Category: Performance

Introduction

Hotel business is a service industry where we don’t sell any products. We get paid for our services. There are so many things that count and affect the performance of a hotel. For example the look of the hotel, the interior, the staff, the room settings, cleanliness, room tariffs, the food, facilities, etc. Apart from these, advertisement is also a must. The staff is the backbone of hotel industry. Kim Hoque (2002a) is of the opinion, “ The only unique asset of a commercial hospitality operation is the staff at the end of the delivery syatem.” (Hoque, 29)

Analysis of the present situation

For any service industry, guest satisfaction is of utmost significance. Our valued guests have been impressed with the tariff of our rooms. We gave our best services with the added advantage of low prices and this helped us in getting more customers.

Price: According to a survey in which five hotels were considered, our hotel had the most economic rates. In fact our rates have been same the whole year round. Not only this, our room tariff is the same for the whole week even. Other hotels increase their tariff during the weekends. This gesture of our hotel has helped us in generating more customers. Our occupancy rate in the last month was 68.2% for weekdays and 68.23% on weekends. For the same month, the second highest occupancy rate amongst the five hotels was 56.42% for weekdays and 55.47% on weekends. Our market share was 26.41% for weekdays and 26.95% for weekends, by the end of first year.

Product: Hospitality is the only product of any hotel. Hospitality includes service, cleanliness, the quality of food and beverages, and comfort. We have never compromised on the cleanliness and the quality of our food and beverages. Manpreet Singh expressed his views, “The fine accommodation and service are provided to the guest so they are pleased with the hotel. The guest satisfaction is its primary object and the hygiene factor must always be present in the hotel.” (Singh). But due to remarkable decrease in our hotel’s profits, the management hasn’t been able to invest in the refurbishment of the hotel. But we have always strived hard to sustain this slump in the business. We give more attention to the cleanliness and maintenance so that things don’t look weary.

Promotion: Until June, we had no sort of advertisement. Even then the occupancy rate of our hotel was the highest. This was possible because of the “word of mouth” publicity. But in spite of this, our hotel was making only marginal profits. So we started some advertisement campaigns and the results started showing by October.

Quantity: Due to the advertising, our occupancy rate shot up from 78.04% in June to 83.18% in October, on weekdays. The guests were also happy because they could find us easily.

Human Resources: Staffing numbers: The forecasted overall staff was supposed to be 98 whereas the actual number of elected staff was 151 i.e. an excess of 54.08%. A close scrutiny shows that the areas where excess staff was employed are front office, room attendants, and service attendants. Actually speaking, this increased number helped us in serving our guests in a better way. But this increased the costs also.

Staff quality: Most of the staff was given ample training in order to improve the service. The competence of such staff has been 100%. It was felt that certain departments didn’t need training. Unfortunately, the competence of such departments has been very poor. Owing to these non performing departments, the average competence level of the staff dropped to 70.33%. Kim Hoque (2002b) showed his concern, “How effective the hotel is in achieving its quality enhancer goals is open to question. Of the 5 percent of guest questionnaire replies expressing dissatisfaction, many complaints concerned staff-related issues rather than technical issues.” (Hoque, 104)

Staff costs: This year $44,700.00 were spent on the training of staff.

Facilities: Offer and condition: Due to the recent refurbishments, the annual guest satisfaction has been 35%.

Stockholders: ROI and security:The return on investment of the owner’s equity is -9.06 %. This is not a good sign. The market index reports are also not encouraging. As per the index the ADR index raised from 55.73 in April to 75.28 in December i.e. an increase of 35.08%. Occupancy rate for our hotel dropped from 139.14 in January to 121.50 in December i.e. a decrease of 12.68%. The RevPar index dropped from 108.60 in January to 92.81 in December i.e. decrease of 14.54%. Mark Woodworth, president of Colliers PKF Hospitality Research put his views in words, “when RevPAR is driven by rate growth, the value is 1.5% higher than when it driven by occupancy.” (Woodworth)

Objectives to be reached at the end of next year

Price: I am of the opinion that the prices should be increased marginally for direct bookings. This will increase our overall revenue.

Product: The management should decide on allotting some funds for refurbishing. This will change the appearance of our interiors and will increase guest traffic.

Promotion: Last year we started little advertisement when we were half way through. Next year we should give the required leverage to advertisement and promotion. Simple word of mouth is not enough.

Quantity: We hope to increase the occupancy rate of our hotel by various means such as getting the refurbishment done, better service, providing lift, better trained staff, etc.

Human Resources: Staffing numbers: The number of staff that was in the last year was not required actually. So this year we should decrease the staff.

Staff quality: We should provide ample training to all the staff from all departments and not like last year. Those untrained workers had decreased the competence rate.

Staff costs: We should not cut on the staff cost (for training). Reduction in staff is different but reduction in the training can harm the hotel in the long run.

Facilities: Offer and condition: We should do some refurbishing and install a lift. These two are the most important things to be done at the moment. Apart from these, we can renovate our swimming pool, have a proper gymnasium, have a small kid section, etc.

Stockholders: ROI and security: Stockholders of any company first of all look at the Income statement. If the figures are good, they will continue with the company else they might withdraw their share. This may prove fatal for the company. Last year’s market index was not encouraging. In the next year we should take care and help in improving our hotel’s Income statement figures so that ROI seems to be good.

Operational plan

Sales prices and product definition: As mentioned earlier, hospitality is the only product (service) of our hotel. All services come under it. We have noticed that our rates are the lowest amongst the five hotels that were part of the survey. Now since we plan to do the refurbishing and interior decoration, I propose an increase in the room tariff by at least 10%. The rate for travel agents should be the same. This will give them the reason to send customers to our hotel. Further, we should improve the quality of our food also. I am not saying that at present it’s not good but there is always a scope for improvement. Once the quality is improved, the rates of food items can also be increased. According to Juliette M. Boone “Overall, the executives agreed that in the past five to ten years, consumers from nearly all market segments have become more demanding when it comes to food and beverage quality and the dining experience.” (Boone, 2008). Other services that we may improve are the swimming pool, a gymnasium, a children’s play room, etc.

Staff: Last year we had excess staff that resulted in excess expenditure. But since this year we are expecting a growth in the number of customers, we will require more staff but not to the last year’s extent. So I propose a cut in the staff to the tune of 15%. The overall wages will come down. Training should be provided to all the staff members, irrespective of the departments. This will increase the competence and our customers will be served better.

Advertisement action plan: Advertisement and promotional campaigns should be launched immediately. We should advertise in the media such as newspapers (classified section), television (local channel), hoardings in and around the city (especially at tourist spots, train and bus stations). Distributing pamphlets would be a good idea as well. Another way of promotion could be keeping hotel brochures at the lounge so that any one sitting there can have a look. The budget that I propose for advertisement and promotion is $100,000.00. This amount may seem to be exorbitant but the results will garner more profit. We should keep in mind that our hotel guests are mostly from other cities and the main rush is during the vacations of school going children. So we should concentrate to advertise during these months only.

Refurbishment decisions: It would be significant to redo the complete interior of all the rooms. This includes the furniture as well. The lounge should be beautified because first impression is the last impression. As soon as any customer enters our hotel, he or she should feel the warmth and comfort of our hospitality.

Investment decisions: For all the improvements mentioned above, a lot of funds will be required. So I don’t think the management should decide on investing anywhere at the moment. In fact the management should try and disinvest a major part of the hotel’s investments that have been done elsewhere. This will ease the urgency of funds.

Loan requests and reimbursements: In lieu of availability of funds, we can apply for loan from banks. In case the management is not able to disinvest, we will require at least $1,000,000.00. The repayment should be such that it doesn’t bother us. It should be a long term loan. I don’t think it would be a problem for us to pay $25,000.00 per month. So within a period of three and a half years, we shall be able to repay the loan.

Reference List

Boone, MB 2008, Increasing Importance of Hotel Food and Beverage is Reflected in Food & Beverage Staffing Trends, Web.

Hoque, K 2002a, Human Resource Management in the Hotel Industry, London: Routledge.

Hoque, K 2002b, Human Resource Management in the Hotel Industry, London: Routledge.

Singh, M n.d., Careers in Hospitality, 2011. Web.

Woodworth, M n.d., Hotel Industry Quotes from ALIS 2011, Web.

Objective

The Objective of the experiment was to determine the fuel consumption of the Chevrolet 4.3 liter engine as a function of coolant temperature, load, and speed using the Latin Squares method and also predict the performance characteristics of a fictitious vehicle based upon engine performance data gathered.

Introduction

Engine testing is an integral part of any engine manufacturing industry. Engines are normally tested by the manufacturing company and sometimes an independent organization to affirm that indeed they perform as per their documented specifications. Most documented d performance ratings however do not specify the conditions under which such performance is achieved. Many manufacturers only give the best performance but without the conditions. In engine testing, however, the conditions must be set and specified to give an accurate indication of exactly how the performance is attained. Engine tests that have been carried out have shown that the rated performances can normally not be achieved under regular operating conditions. Measuring engine parameters is also vital in the creation of more advanced technologies.

According to Gitano (2006)” Testing of engine performance is often important in the development of engine and fuel technologies. Many parameters affect an engine’s performance: the basic engine design, compression ratio, valve timing, ignition timing, fuel, lubricant, and temperature”. Several parameters of engine performance can be measured but the main and most important test is the power test. In this test, the power of the engine is obtained. Power can however not be measured directly; this then implies that other parameters that are directly related to power are measured then used in the computation of power. Power can be computed by obtaining the product of torque and angular velocity.i.e.

Angular velocity in revolutions per minute on the other hand is given by

The two equations can be combined to get

From this formula, we can therefore obtain the power even though it is not measured directly. The torque and angular velocity are measured d and fitted in the above equations to get the power.

Engines can normally be tested in the lab; this is made possible by connecting the engine to some kind of load that strains the engine. In most cases, this loading is provided by a dynamometer which allows the researcher to widely vary the load on the engine. The speed and torque can also, therefore, be varied and measured once the engine is coupled to a dynamometer.

The angular velocity is measured using a device called a tachometer. Most modern tachometers measure the rotational speed optically and display it on a display unit. The more recent digital tachometers have very high accuracies and are easy to use (Testing the Performance of Model Engines, 2005).

Torque on the other hand is measured by applying some force on the engine through the dynamometer. The force is in most cases taken up by a force transducer which gives the measured strain. This strain is amplified to give out a voltage that varies directly with the load. The measured torque is the same as that on the dynamometer.

The throttle position should also be measured. Throttle position sensors are fitted to most engines and this is used to obtain the throttle position and pass its position to the electronic control unit. Throttle position sensors in engines with carburetors can be fixed onto the throttle linkage so as to measure the throttle position directly. In a typical test, the dynamometer is set to a specific speed, and the torque is measured about the throttle position. It is also possible to keep the throttle in one position and vary the speed. Values of varying speed and torque can then be measured and used to compute the power using the above-mentioned relationship (Testing the Performance of Model Engines, 2005).

Fuel consumption can also be measured during the testing as this is a very important parameter. Other parameters that can be measured during the length of the test are airflow and exhaust emissions. Analysis of this can give an idea of just how efficiently the engine is running. Temperatures at several points around the engine may also be measured to establish factors like the optimum operating temperature and if there is overheating. Air/Fuel ratio is another very important factor in engine testing. Different test conditions result in different air-fuel ratios which in turn results in variation in all the above measurable and computable parameters like power, fuel consumption, and overall engine efficiency.

According to Gitano (2006)”Engine testing requires fairly low data-rate measurements because all variables are averaged over several engine cycles. Data acquired in this manner are referred to as “cycle-average data.” Relatively slowly changing values, such as engine speed, fuel flow, engine temperature, and manifold pressure, are measured directly. Torque fluctuates over the cycle of an engine, being highest during the power stroke and lowest during the compression stroke. Fluctuating signals may be filtered electronically to remove this higher-frequency variation, and various digital techniques (such as exponential averaging) may also be applied once the data has been acquired”.

It is worth noting that all instruments used in the experiment must be properly and severally calibrated to ensure that the results are as accurate as possible. Several readings must also be made so as to get values that are consistent and accurate. The several calculations and graphs involved make it necessary to have a proper computer to work out all the calculations accurately (Korcek & Jensen, 2001).

In general, engine testing is vital in mechanical engineering because it helps in the progression of technology continuity in improvement to producing more and more efficient engines. Technologies like variable valve injectors were developed as a means of increasing fuel efficiency in petrol engines after research on fuel efficiency using such tests. Engine models are also revised after findings in engine testing leading to the development of more efficient systems (Büchi & Freunberger, 2007). High-performance engines used in sports cars have also been developed after much research and engine testing. Combined power and fuel efficiency testing is key in helping develop engines that strike a good balance between high power and optimum efficiency. Exhaust emissions and their effect on the environment have been a very contentious issue with the ever-increasing environmental awareness. Engine testing can obviously not be ignored in this regard because fuel-run engines are major pollutants of the environment and everything must be done to ensure that the effect of these emissions is reduced or eliminated altogether (Laser & Larson, 2009).

Procedure

Equipment

The equipment used in these experiment included:

• Chevrolet 4.3 liter V -6 engine, Dyno-mite dynamometer with computer data acquisition system

Methodology

Fuel consumption for torques of 40, 80, 120, 160 ft-lbs, Engine speeds of 1800, 2400, 3000, 3600 rpm, coolant temperatures of 175, 185, 195, 205, and O F were measured in accordance with factorial testing procedures. The fuel consumption rate for one extra point not in the Latin squares arrangement was also measured. The sweep function allowed the dyno operator to select a pre-programmed load to allow the engine to operate through the allowable engine speeds. The maximum safe speed allowed in this test was 4000 rpm. We set the lower limit of the engine speed to 1600 rpm and the upper limit to 4000 rpm. The rate of engine speed increase was 200 rpm/sec. After setting the lower rpm, we increased the engine speed slowly to allow the dyno to load and maintain speed. Once the throttle setting was finalized, we engaged the sweep test. The data from previous experiments had resulted in the following relation for torque in foot-lbs and engine speed in rpm:

The Figure below gives a schematic of the apparatus:

• Torque = 3Xl0-9rpm3 -5Xl0-5 rpm2 +0.22rpm -40.974

The data gathered allowed us to construct the power and torque curves for the engine to be used to predict the performance of the vehicle. The testing was performed at a coolant temperature of 205 F.

Fuel Calibration

Tests conducted in previous years showed that the fuel calibration of this dynamometer was off. The screen displayed the amount of fuel being consumed by the engine as the difference between the amount of fuel pumped from the fuel tank (meter a) and the amount of fuel being returned to the tank (meter b). The formula used to correct the fuel flow rate is as follows:

• Fuel Consumed = -0.0031×3 + 0.2055×2 – 2.5919x + 18.767

Where x was taken the fuel consumption difference of (a-b) from the data files. After recording the fuel usage from the computer files, we applied the correction factor to account for the deviation. Please note that the units were in lbmlhour.

Methodology for vehicle performance calculations

The assignment for the performance testing of the Chevrolet 4.3 liter V-6 engine was to predict the vehicle performance based upon the data collected from the engine and apply established engineering principles to determine the characteristics of a fictitious vehicle.

To predict the acceleration rates of the vehicle, we determined the force required to accelerate the vehicle based upon F=ma. At any given instant, the forces must be in equilibrium. Thus, if a vehicle is at cruise conditions, the force transmitted by the drive wheels to the roadway should be equal to the drag force on the car exerted by the vehicle’s motion through the air and the rolling resistance which is a function of tire construction and the weight of the vehicle. Under acceleration, the force available to accelerate the vehicle is the difference between the required force to maintain the vehicle at the present velocity and the force necessary to accelerate the vehicle, F-ma.

In this experiment, we collected the performance data for full-throttle operation. By utilizing the transmission and final gear ratios along with the rolling radius of the tires, we were able to determine the propulsive force at any given instant. For purposes of this experiment we assumed that the parasitic power loss for the engine and drive train is given by the following expression:

• PowerparaSiliC = 3XIO-5(V3) – 0.0065(V2) + 0.5505(V) + 17.089

Where: power was in horsepower and V is in mph

The rolling resistance power requirement is given by the expression:

• Power rolling = 0.0083(V2) + 0.1419(V) + lXl 0-11

Where: power was in horsepower and V is in mph

For fuel economy calculations at a constant speed, we determined the power requirements and compared them with the fuel usage as determined by actual testing.

Reference list

Büchi , F. N., & Freunberger S. A. (2007).On the Efficiency of an Advanced Automotive Fuel Cell System. Fuel Cells 7(2), 159-164.

Gitano, H.(2006).Small Engine Dynamometer Testing. Performing Dynamometer Testing on Combustion Engines. Web.

Korcek, S., & Jensen, K. (2001).Maximizing the fuel efficiency of engine oils: The role of tribology. Tribotest 7(3), 187-201.

Laser, M.,& Larson, E.(2009). Bruce Dale Comparative analysis of efficiency, environmental impact, and process economics for mature biomass refining scenarios. Biofuels, Bioproducts and Biorefining 3(2), 247-270.

Suresh, A. V., & Mehta, A. K. (1993).A new test technique for the laboratory evaluation of energy-efficient engine oils. Lubrication Science, 5(4), 283-294.

Testing the Performance of Model Engines. (2008). Web.

Research Questions

Does the use of technical information in the classroom improve students’ performance?

Study Objective

To compare the performance of students taught using information technology against those who use conventional methods of teaching.

Variables

Independent

Information Technology

Traditional methods of teaching

Dependent

Academic performance

Hypothesis

Null Hypothesis

The use of information technology in educating students does not improve academic performance more than the use of traditional methods does.

Alternative Hypothesis

The use of information technology in educating students improves academic performance more than the use of traditional methods.

Study Design

This study will employ an experimental research design to establish the effects of information technology on the academic performance of students in different study levels. The researcher will identify one nursery school, one primary school, one high school, and one university to enroll participants in the study. The participants will be assigned to two groups, namely, the experimental and control. The researchers will administer the ‘treatment’ (information technology method), while the control group will be taught using traditional methods rather than information technology methods (Muijs, 2011).

Randomly selected teachers will be trained to use information technology for a month before the beginning of the term or semester. During the term or semester, the groups will be taught separately using information technology and traditional learning methods respectively. Then, after the end of term or semester, the participants will be given some exams depending on the class and level.

Study Sample

The researchers will enroll between 600-1000 students to form different levels of study including nursery, primary, secondary, and university. The researcher will obtain a permit to undertake the study from the office of ethics on the research board in the county of study.

The inclusion criteria involve schools that have not adopted information technology in their teaching. The classes should not be the first or last grade or class in the respective level of education. The research will disregard whether the chosen school is public or private. Participants must derive from one class or grade in the same faculty of study.

Data Collection

The results of the participant will be evaluated after the period of the study will be over to identify the difference in performance between the groups in specific schools. Besides, the performance of the student after the end of the research will be compared with the performance in the previous term or semester.

Data Analysis

The researcher will use the results of the test administered at the end of the study to determine the effects of information technology on the academic performance of the two groups. The researcher will find the mean of the performances of the participants in the two groups and perform a t-test to establish the statistical significance of the results in the individual level of study (Cohen, Manion, and Keith, 2007). Similarly, the researchers will find the average of the performances of individual participants in the previous term, before the study, and perform a t-test to establish the statistical significance of the difference in the performance, and establish the impact of information technology on the education system (Bryman and Cramer, 2005).

Moreover, the results across all the study groups will be evaluated to establish the difference in the impact of adopting information technology in different levels of study and the relationship to the characteristics of the students.

Research timeline

Teachers selected for research and assigned to experimental groups will be trained on instructing using different forms of information technology including video conferences, and groups. This training will begin on July 1 and end on July 31. Students will be grouped into two a week before the start of the semester or term, that is, from August 23 to August 30. On September 3, the research study will begin with the classes administered simultaneously for the two groups.

This exercise will take continue for the entire term or semester. The participants will be given an exam by the end of the semester, same time as the other students in the school, set by especially for research purposes. The exams for both groups in respective schools will be the same. The examination will start on November 14 and end on the 28th of the same month. Finally, the analysis of the study will take two weeks starting from December 6 and ending on the 20th same month.

Budget

Reference List

Bryman, A., & Cramer, D. (2005). Quantitative Data Analysis with SPSS 12 and 13: A Guide for Social Scientist. East Sussex: Psychology Press.

Cohen, L., Manion, L., & Keith, M. (2007). Research Methods in Education (6th Edition ed.). Oxon: Routledge.

Muijs, D. (2011). Doing Quantitaive Research in Education with SPSS. London: Sage Publication Ltd.

Introduction/Background

The issue of the safety of aviation is of critical importance because aircraft crashes, runway excursions, and other types of air accidents always remain a potential risk to the lives of both passengers and aircraft staff. However, there is one more aspect to this problem. Air transport is perhaps one of the most feared types of transport among the population. Thus, to persuade clients to use an aircraft, it is crucial to keep the risks as low as possible; otherwise, many people might decide not to use air transport at all. Air transport is much safer than most types of surface transport (Wiegmann & Shappell 2003); nevertheless, lowering the risk of air accidents always remains an important problem.

A significant proportion of accidents in the air industry is related not too technical issues but to human factors. Chang, Yang, and Hsiao (2016) identified a range of human factors that may impede a pilot’s performance and ability to manage an aircraft that lands or takes off; these touch upon a wide array of individual peculiarities and social relationships of a pilot; van Dijk, van de Merwe, and Zon (2011) studied the impact of eye movement on situation awareness; it was found out that different regimes of sleep may significantly affect the physical state of pilots, increasing the chance to err (‘Aviation human factors’ 2015); and Davey (2004) researched the impact of educational atmosphere on the future qualities of pilots which may affect their performance.

However, it is reasonable to expect that there are gaps in the literature related to this topic. Furthermore, the progress of technology and developments in education might allow for compensating for human factors that we’re incapable of being addressed before, and avoid possible errors; such factors and errors might need to be studied in more detail to be dealt with properly. This corroborates the need for further studies of human factors which would identify the most relevant factors, permitting for finding ways and providing recommendations aimed at preventing the related risks.

Aims

By the end of the project, it is aimed to contribute to the research about the human factors affecting the performance of pilots by studying these factors and considering the newest technological developments permitting for compensating for their adverse effects.

Objectives

• To review the existing studies about the effect of human errors on the pilot performance.
• To identify the currently utilized courses and training that pilots gain to improve their skills.
• To explore the new programs and methods of training which have the potential of enhancing the pilot performance and increasing the levels of aircraft safety.
• To analyze the most prevalent reasons for the recent accidents in the aviation industry, and the role of human errors in these incidents.
• To consider the developments in the aviation industry that might allow for better pilots’ performance.
• To collect and examine data related to the impact of human factors on pilots’ performance by employing a survey for pilots.
• To suggest several ways to avoid human errors and provide a better pilot performance to increase in-flight safety.

Outcomes

By the end of the project, it is expected to reach the established objectives of the study, which might allow for finding ways to increase the levels of safety of individuals who travel or work on aircraft. As a result of the project, it is desirable to provide a review of the current studies about the issue of human errors, and identify the impact of these mistakes on the performance of pilots; to describe the peculiarities of pilot training programs and consider the effect of the curricula and training on the skills and abilities of pilots, as well as to take into consideration the new developments in this field; to make an overview of new curricula and methods of training which might help pilots avoid mistakes or lower the influence of human factors on the aircraft safety, and to come up with several ways that might be useful in lowering the rates of human errors in the aircraft industry.

Research Approach/Methodology

The part of the study that involves processing the already existing knowledge will employ a deductive approach. More specifically, a review of research literature will help achieve most of the established objectives of the study. The limitations are those of a secondary study; the collected data might be heterogeneous and incomplete, its quality will not be controlled closely, etc.

On the other hand, collecting and examining the data about the impact of human factors on pilots’ performance will employ an inductive approach. Inferential procedures may be utilized to conclude such a study. The limitations include limited capabilities of data collection, possibly small size, and the approximation of the results.

Risk Analysis and Contingency Planning

The review of the literature does not suggest that any risks might become a significant source of trouble while conducting this study. On the other hand, the collection of data from pilots is related to several difficulties such as the need to find a large enough sample. However, it seems that these and similar issues will not become significant sources of risk.

Resources

To carry out the described study, it will be needed to collect the data related to the influence of human factors on flight safety. The data will be obtained primarily from research studies the results of which were published in peer-reviewed academic journals. A vast array of such articles may be accessed by utilizing the university library. In particular, several scientific databases (such as ProQuest or EBSCOhost) might be employed to find the desired data. In addition, because it will be required to collect information about recent accidents in the aircraft industry, it might be possible that a need in reviewing online news related to the topic arises.

Of course, it will also be necessary to collect primary data from pilots of aircraft by using a survey.

Code of Ethics

The possible ethical considerations of the study which is offered in this paper are related to the fact that the data which will be collected from the pilots might be related to their features. However, during the study, it will be attempted to collect only that data that has an impact on the performance of a pilot. It is clear that before conducting the survey, the researcher will have to obtain informed consent from those who will be the respondents of the study. It will also be necessary to ensure that the privacy of the participants is kept.

Reading/References

‘Aviation human factors related industry news’ 2015, Aviation Psychology and Applied Human Factors, vol. 5, no. 1, pp. 67-69.

Chang, YH, Yang, HH, & Hsiao, YJ 2016, ‘Human risk factors associated with pilots in runway excursions’, Accident Analysis and Prevention, vol. 94, pp. 227-237.

Davey, CL 2004, ‘The impact of human factors on ab initio pilot training’, Gender, Work and Organization, vol. 11, no. 6, pp. 627-647.

Van Dijk, H, van de Merwe, K, & Zon, R 2011, ‘A coherent impression of the pilots’ situation awareness: studying relevant human factors tools’, International Journal of Aviation Psychology, vol. 21, no. 4, pp. 343-356.

Wiegmann, DA, & Shappell, SA 2003, A human error approach to aviation accident analysis: the human factors analysis and classification system, Ashgate Publishing Company, Burlington, VT.

Rodney Brooks invented Baxter in 2012. These are robots that perform small repetitive jobs such as packing and sorting items (Baxter with intera, 2014 ). They are cheap enough for companies and individuals who cannot afford enormous and more sophisticated robots. They captured my attention because they are not huge and ugly as ordinary robots. This technology will impact the performance of companies by reducing the time spent on repetitive duties such as packing. In case my employers buy this robot, I will not be affected personally, but the performance of the entire company will improve. This invention has the potential for improvement. Its inventors can make a bigger and more efficient robot that can work on more involving jobs.

Advantages

• Hastens the handling of tasks in companies
• It does not require special skills, except when installing the robot.

Disadvantage

Replaces human beings: causes unemployment.

References

Baxter with intera 3 (2014). Web.

Introduction

There are many designed websites for nations/states, profit and non-profit making organizations as well as for individual that are currently in use. The designing and establishment of these websites have been a key trend since the commencement of the world’s gradual transition to the new era of information technology.

Although there are numerous reasons which trigger the designing of websites, it is viewed that the only major one is to increase productivity, whether it’s for a state, profit and non-profit making organizations or individuals.

However, it has been noted that many websites had been closed and a good percentage of those remaining ones still have poor performances. Simply, the implication of this is that most of the websites are of poor and low standard quality to attract the right number of traffics and meet its needs (Andreasen and Kotler, 2007). Therefore, this work focuses on the evaluation of Bill and Melinda Gates foundation’s (B & MGF) website which has the URL.

The main purpose of the work is to assess the key design features to attract the targeted audiences and improve the performance of the website for an organization established in an area viewed as being hard to attract adequate clients, and most important that is founded in healthcare service provision.

Background

Bill & Melinda Gates Foundation organization founded in 1994 was established to provide humanitarian services of health and housing care. For more than a decade, the organization has invested large sums of funds to meet health requirement needs for people both in the developing and developed countries. Generally, the organization has helped thousands of people suffering from illnesses and/or those who are poverty stricken to keep them live healthy and under improved living standards.

Reasons that makes B & MGF’s website effective

Structure and organization

The successful performance of the B & MGF’s website is associated to a number of factors which generally bolsters other types of businesses. The website design is one of the factors promoting its effectiveness and efficiency.

It appears to be less crowded with many items in the front page and the subsequent pages. This enables easy loading of the website, hence encouraging quick opening of the places or material by the targeted audiences (Brinckerhoff, 2010).

Thus, this simple design of the website saves time for the clients, and persuades the customers not only to visit the different web pages/ areas of the site, but this also promotes their future re-visitation on the site. The organization’s title name is clear inscribed at the top left, thus connecting it to its major driving philosophical statement at the top most right corner.

The placement of the organization’s title and the slogan of what the organization values most are unique. The organization has further supported the kind of services it is offering through the providing of a list on the section of topic, whereby, the services are divided into their related categories (Garfield, 2009).

Market expansion by product creation and advertising

In order for the website to serve its clients effectively, the organization has also developed a several programs, some of which are regionally designated while others are aimed at drawing clients from the global realm.

The organization has developed health and development programs as the two major products to attract clients nationwide. On the other hand, there are those programs which are specifically aimed at fostering health for the people residing in the United States.

Considering the fact that this is globally oriented organization and the nature of services or products it offers, the organization has penetrated into all continents of the world, meaning that it has overcame most of the barriers/ resistances offered to other commercially operating organization in the international trades (Greenfiel, 2002).

The organization easy penetration towards its achievement in the curbing those global problems has not been an arbitrary one, but this has been facilitated through proper integration of the strategy of partnership with other relevant organization which during the organization operations support it directly or indirectly.

The website has therefore been promoted through its linkage strategy with other organization’s site offering healthcare services including institutions like Harvard school of public health. Moreover, the organization’s website has been made effective by the fact that it is linked to several advertising and media organizations such as the KDNA radio and other press publishing organizations (Ries and Trout, 2009).

Conclusion

The B & MGF website is one of the uniquely designed websites. Though it is not wise to strictly say that it’s the best of all the websites, it bears most of the needed features to capture a high market share from the global realm.

References

Andreasen, A. and Kotler, P. (2007) Strategic Marketing for Non-Profit Organizations. New Jersey: Prentice Hall

Brinckerhoff, P. (2010). Mission-Based Marketing: Positioning Your Not-for-Profit in an Increasingly Competitive World. Wiley

Garfield, B. (2009). The Chaos Scenario. Stielstra Publishing

Greenfiel, J. (2002). Fund Raising: Evaluating and Managing the Fund Development Process. Wiley

Ries, A. and Trout, J. (2009). Positioning: The Battle for Your Mind. McGraw-Hill

Abstract

The journal article The Effects of Integrating Mobile Devices with Teaching and Learning on Students’ Learning Performance: A Meta-Analysis and Research Synthesis by Yao-Ting Sung, Kuo-En Chang, and Tzu-Chien Liu, and published by Elsevier Ltd. in November 2015, presents different findings on mobile devices integration and education effectiveness from previous case studies. It gives a detailed summary of past literature on the topic, published between the years 1993 and 2013, which studied the integration of mobile devices into education and their impacts on learning and teaching activities. It also provides a meta-analysis of the effects of the size of different journal articles, which have provided an analysis of computer use in learning.

The article by Yao-Ting Sung, Kuo-En Chang, and Tzu-Chien Liu has also provided an overview of the general users of mobile devices and the sites they frequently visit. It also gives an outline of the negative and positive impacts of integrating mobile learning at different levels. The proposed research paper will present a summary of the principal contents of the journal article, in a revised and easier form for clarity. It will also present positive sides as well as the critique of the journal article.

In particular, this research paper will attempt to explain two mathematical formulas employed in the journal article, which are Cohen’s d formula used in calculating the effect sizes of the study and a Comprehensive Meta-Analysis formula. The proposed research will explain the relevance of the two formulas about the content of the journal article. Particularly, this paper will focus on the authenticity of the findings and how the two formulas were used to present similar results.

Introduction

Improved information technology and innovative ideas have contributed to the introduction of mobile learning into the teaching curriculum over the past two decades. Specifically, the paradigm shift has been accelerated by the advent of mobile device technology in the last decade. This, in turn, has promoted exploratory learning, cooperative learning, and game-based learning, which can be conducted in different areas including classrooms and outside classrooms.

According to Ary, Jacobs, and Razavieh (2012), computer-based learning has been promoted by the existence of various portable devices such as cell phones, laptops, tablets, and e-book readers [3]. At present, these devices have become part and parcel of educational instructional delivery across the globe. Factually, most of the devices have been modified to support learning in elementary and advanced educational environments.

Table 1. Different forms of technology-aided learning.

The authors of the journal article The Effects of Integrating Mobile Devices with Teaching and Learning on Students’ Learning Performance: A Meta-Analysis and Research Synthesis have focused on researching and explaining the various ways in which mobile devices have been integrated into learning and teaching activities. They have also provided reviews of various articles that have information about how mobile devices have been integrated with learning and teaching.

Through a systematic review of past literature on the integration of mobile devices and education effects, the authors were able to capture previous research findings from a myriad of scholars. Several other authors have also made contributions to the content of the journal article. For instance, the authors utilized a study by Penuel (2006), which found out that education systems having a design/program for integrating mobile devices with learning were few and unevenly distributed [28]. Sung, Chang, and Liu (2015) also employed the studies of Zucker and Light (2009) who concluded that although integration of mobile devices in education is a positive step, it did not enhance the thinking levels of students [32] [40].

The authors of the journal article employed the method/technique of both electrical and manual searches to obtain relevant journal articles published between the years 1993 and 2013. These articles were then reviewed to determine the extent of integration of mobile devices in learning. Most of the electronic articles with relevant information were obtained from the Education Resources Information Centre (ERIC) database and the Social Sciences Citation Index database of the Institute of Science Index (ISI). The sites have published and reviewed scientific studies that were carried out scientifically by academic scholars.

Data analysis was done using the Cohen’s d formula, which was obtained from Cohen (1988) and Lipshitz, Friedman, and Popper’s (2014) studies [14] [25]. The Comprehensive Meta-Analysis formula was also derived to analyze quasi-experimental results, which had pretests. In addition, the Fail-safe N by Rosenthal (1979) was applied in the analysis to eliminate biases since it considered the side effects from unpublished data in the previous studies [30].

This helped to minimize the overall effects of insignificant levels. Through reviewing several journals from the past two decades, the paper has provided a detailed analysis of the advantages and disadvantages of integrating electronic devices in learning and teaching activities. The use of manual and electrical search techniques further enabled them to obtain relevant information for their study. Specifically, the electrical technique allowed Sung, Chang, and Liu (2015) to narrow their search keywords [32]. This helped them to obtain information on mobile-related and learning-related searches.

The detailed information in the journal article has been reviewed and cited in other works. It has allowed several other researchers to build on their topics. For instance, Heflin, Shewmaker, and Nguyen (2017) utilized information from the Sung, Chang, and Liu (2015) study in writing their article about how mobile technology influences students’ attitudes [22] [32]. Other studies also employed the data analysis formula utilized in this paper to carry out a meta-analysis of their respective studies. The critique of this journal article is that the research was based exclusively on secondary data, that is, publications in both electronic and paper prints.

According to Chen, Tan, and Lo (2013), and Fernandez-Lopez et al. (2013), more relevant information can be obtained if research is extended to actual learning institutions where the learning performance of students using mobile devices would be directly observed [12] [19]. Information technology changes rapidly with time. Therefore, some older articles may contain outdated information.

The proposed report will review the principal contents of the journal article in a revised and more elaborate form to enhance easy understanding. The report captures a summary of the results obtained and the information presented in tables within the journal article. Relevant examples and figures will be included to ensure the smooth flow of the report. This will ensure an easy understanding and grasping of the concepts of the paper at a glance.

The study discusses the proper data analysis, good writing style, and proper work format employed in the paper. This report will also discuss how Sung, Chang, and Liu (2015) researched their study topic to fulfill their goals and objectives through reviewing documents that are two decades old and have information about mobile devices use in learning activities [32]. The shortcomings and inadequate information arising from the journal article will also be discussed in this report.

Preliminaries

This research will be based on learning or teaching strategies, pedagogical issues, and evaluation methodology through the application of the Cohen’s d formula in calculating the effect sizes of the study and a Comprehensive Meta-Analysis formula. As captured in table 2, the analysis will be based on six components of the activity theory, which are subjects, objects, tools/instruments, rules/controls, study context, and communication/interaction. Dependent variables are categorized into learning achievement and affective variables. Andreadis (2009) notes that learning achievement variables measure problem solving, retention, and knowledge application, which forms part of the cognitive outcome [9]. The effective variable is the quantification of participation, interest, and motivation.

Table 2. Variables of the study.

The Cohen’s d formula is summarized as

Where x¹ and x² are mean scores while n¹n² and are sample sizes. The s¹² and s²² are the variances of experimental and control groups. According to De-Joodea et al. (2013) and Chiu and Liu (2013), for quasi-experimental and experimental pretests, the posttest would mitigate any selection bias [13] [16]. Thus, the developed comprehensive Meta-analysis formula is;

ES_Pre/Post Test Two Groups = (X1 _Post – X1 _Pre) – (X2 _Post – X2 _Pre) / SD_Post

Where X1 _Post and X1 _Pre are experimental groups mean scores for posttest and pretest. The X2 _Post and X2 _Pre are control group mean scores for the pretest and posttest. The SD_Post was computed as follows:

SD_Post= (n_2Post – 1)s²_2Post + (n_{1 Post} – 1) s²_1Post/ (n_2Post + n_{1 Post}-2)

Where n_{1 Post} and n_2Post are experimental and control group sample sizes. The s²_1Post and s²_2Post are experimental and control group variances in the posttest. Therefore, the effect-size was integrated by the use of sample weights to derive a Hedge’s gas;

Topic

Continuing research on the topic will be good since it broadens the scope and presents recent information about the impact of integrating mobile devices in learning. Moreover, it will provide a meta-analysis of the side effects of the viewed articles. It will synthesize quality information concerning the integration of mobile devices into the education sector. Through the continuation of the topic, as noted by Edwards, Rule, and Boody (2013), a researcher will get to understand the major users of mobile devices in the education sector since it explores the effectiveness of integrating mobile devices into education [18].

This will enhance any understanding of the advantages and disadvantages of mobile technology and also suggest ways of improving mobile learning activities. The analyzed journal article has quality information such that it has been cited by around 142 articles in the computer and education field. For instance, Heflin, Shewmaker, and Nguyen (2017) utilized information from this paper in writing their article about how mobile technology influences students’ attitudes [22].

Therefore, the continuation of the topic will greatly enhance the knowledge base and understanding of the extent, impacts, and ways in which mobile device use has been implemented in education systems.

From reviewing these articles, the authors of the discussed topic discovered that mobile technology and the use of mobile devices have been highly integrated into various teaching and learning processes. According to Frohberg, Goth, and Schwabe (2009), this is due to the presence of several different types of mobile devices and wireless networks [21]. This has, however, faced challenges because most mobile device use practices would alter the learning and teaching curriculum of various institutions. Adaptation to these changes is gradual since most people are reluctant to sudden change.

The techniques in this paper were also employed by Chauhan (2016) whose title of the study was A Meta-Analysis of the Impact of Technology on Learning Effectiveness of Elementary Students [11]. Chauhan (2016) conducted a meta-analysis of the impact of sizes [11].

Together with other data analysis methods, it was concluded that technology enhances learning effectiveness. Therefore, the continuation of the topic will create the basis for further research in the field of computers and technology. Also, Best and Kahn (1998).note that more research will fill the knowledge gap created by the current study to improve the scientific literature about computer devices and learning [7].

The journal article’s topic acknowledges that information technology and innovative ideas have contributed to the introduction of mobile learning into the teaching curriculum over the past two decades. The main contribution of the journal article’s findings is that through research, Riconscente (2013), Hwang and Tsai (2011), Runyan et al. (2013), and Penuel (2006) have discovered that very few studies have addressed the issue of effectively promoting mobile learning, despite the advantage of improved mobile technology [29] [23] [31] [28].

The journal article has reviewed two broad topics: programs based on laptop use, and the implementation of mobile technology in education systems. Therefore, continuing further research on the topic will create room for narrowing down each program and its effectiveness in mobile device-aided learning.

While focusing on the laptop-based program, the current approach by Sung, Chang, and Liu (2015) reviews and describes Zucker and Light’s (2009) study, which concluded that laptop integration positively impacted the learning behavior of students [32] [40]. The findings further indicated that it did not enhance the levels of thinking among students, and it did not change the teaching methods used in classrooms. This was considered a drawback in the program of integrating education with laptop use.

A review of Penuel (2006) and Bebell and Kay’s (2010) articles showed that student laptops were mainly used to finish assignments, take notes, and for homework purposes [28] [6]. Web browsers, word processors, and presentation software were the main laptop tools utilized in this case. Bebell and Kay (2010) discovered that teachers modified their teaching methods due to increased access and use of laptops [6]. Therefore, continuing further research on the topic will present the current situation where technology-aided learning has become a norm in most educational institutions.

A review of Fleischer’s (2012) article showed that the time of laptop use by various students varies from several days to several hours a week [20]. Laptops were mainly used for communication and research purposes. It was also noted that laptop use was a challenge since most teachers had to be convinced to alter their previous teaching methods to accommodate a new model of teaching curriculum that incorporated laptop use.

While focusing on the implementation of mobile technology in education systems, the paper reports that Hwang and Tsai (2011) studies concluded that the use of mobile technology in learning increased remarkably in 2008, and the main users were senior students of engineering, computer science, and language art. Mobile technology was mainly involved in research and finishing assignments [23]. Any further study, as captured in table 3, will build on these findings to establish an existing pattern, especially when the variables are interchanged.

Table 3.Topic relevance.

Understand the Topic and Gather Problem

From reviewing the above articles, the findings suggested that mobile technology and the use of mobile devices have been highly integrated into various teaching and learning processes. According to Van-der-Kleij, Feskens, and Eggen (2015), this is due to the presence of several different types of mobile devices and wireless networks [33]. This has, however, faced challenges because most mobile device use practices would alter the learning and teaching curriculum of various institutions.

Adaptation to these changes is gradual since most people are reluctant to sudden change. According to Wong and Looi (2011), and Wang and Wu (2011), most mobile-learning activities were conducted in unofficial places, within classrooms, and offices [36] [34]. Mobile technology has also been employed in research as a reinforcement tool and as an information delivery tool. The minimal use of mobile technology is involved in critical thinking and communication.

A review of Wong and Looi’s (2011) article showed that most mobile devices were employed in seamless learning [36]. This was observed in classrooms, especially in higher learning institutions, offices, and social learning centers. This further supported Hwang and Tsai’s (2011) study which discovered that mobile technology was mainly utilized by senior students such as those in college [23]. The minimal use of mobile devices was observed among primary school students.

Sung, Chang, and Liu (2015) confirmed the above findings by indicating that there is a positive correlation between the integration of mobile devices into teaching and the learning ability among students of different grades, ages, and ethnicity [32]. Hwang et al. (2011) noted that integrating mobile devices in education is a motivational factor to content internalization and performance of learners [24]. Moreover, mobile devices improved instructors’ teaching experience as they made the process of knowledge dissemination simple and straightforward.

Therefore, as captured in table 4, the four identified problems for further study and their significance are technology-aided teaching, technology devices, learning effectiveness, and teaching effectiveness. The four problems are directly associated with the instruments of establishing the impacts of technology-aided devices in the learning process. Specifically, these items capture the actual technology in use, its application, and response from the side of the learner and educator. In the research study, these four items will address the research objective of quantifying the actual impacts of associating technology with education.

About previous studies by Warschauer et al. (2014) and Wouters et al. (2013), the primary assumption is that technology-aided learning has a positive impact on the educational environment from the learner’s and educator’s perspectives [35] [37].

Table 4. Summary of the research items.

From the above table, it is apparent that a lot of research has been carried out on the impact of technology devices on learning in different educational environments. The table presents an analysis of the findings of over thirty previous researches on the topic. In all research findings, Chaiprasurt and Esichaikul (2013), Zhang et al. (2014), Yang et al. (2013), and Zucker and Light (2009) confirmed a positive correlation between the integration of technology-aided learning and improvement in the learning experience [10] [39] [38] [40].

Specifically, the findings suggest stakeholder inclusion to make technology more acceptable and relevant in different educational environments. Among the most common electronic devices identified by scholars in the literature review, there are projectors, mobile phones, tablets, and computers. According to Bruce-Low et al. (2013) and Ahmed and Parsons (2013), these devices come with pre-installed applications such as an e-book shop and soft copies of the syllabus, However, there were no concrete results established in attempting to relate the introduction of the digital syllabus to the effective learning process [9] [1]. This aspect forms the scope of the proposed new research.

Formulate Problems/Hypothesis

The literature review gives minimal information on the impact of introducing a digital syllabus on the learning process. The four issues highlighted in table 4 will be transformed into research problems to develop a new research scope. The first issue is technology-aided learning. Though effectively covered from the aspect of the application in the learning process, there is a gap in how it is developed for effective and sustainable integration. Therefore, the following research hypotheses were created to address the research problem;

• H1₁: Effectiveness of technology-aided learning depends on proper integration of the content on different devices.
• H0₁: Effectiveness of technology-aided learning does not depend on proper integration of the content on different devices.

The above hypothesis is relevant to the proposed research since it will confirm or reject the significance of the integration of different technological devices into the content of learning. Factually, it would highlight basic principles to be observed to make the transition from traditional to digital learning smooth and acceptable among stakeholders. At present, the literature review carried out has not highlighted this aspect in explaining the impact of technology on education and the learning process.

The second item identified in table 4 is the relationship between the technological device used and the outcome of a learning process. The previous studies have identified different technological devices and their use in teaching and learning processes. However, little research exists on the impact of each type of device on education. Thus, the second hypothesis developed from this research problem is;

• H2₂: Different technology-aided learning devices have similar impacts on the outcome of an education process.
• H0₂: Different technology-aided learning devices have different impacts on the outcome of an education process.

This hypothesis will provide an impetus for improving the current set of knowledge on the devices used to facilitate technology-based learning. About the proposed research, this hypothesis will address the implementation aspect of technology-aided learning.

The third item highlighted in table 4 is learning effectiveness from the perspective of learners. This item forms part of the research problem since the findings highlighted in the literature review are inconclusive. Specifically, previous studies have concentrated on technology making the learning process efficient. The scholars are silent on other benefits. Therefore, the proposed research will attempt to identify any other existing benefits. The following hypothesis was developed to address this research problem:

• H3₃: There are benefits of technology-aided education other than improvement of the learning process efficiency.
• H0₃: There are no benefits of technology-aided education other than improvement of the learning process efficiency.

This research hypothesis will address the aspect of stakeholder feedback associating technology-aided learning with progressive education. Specifically, this hypothesis will establish the view of students who are the primary beneficiaries of technology-based learning. In addition, this hypothesis will enable the researcher to put the views of the learners in the perspective of progressive research. The findings will confirm or further the results from previous studies.

The fourth item identified in table 4 is teaching effectiveness. Specifically, this item forms part of the research problem since it aims at identifying the views of instructors about technology-aided learning. The results of the previous studies have highlighted many benefits associated with technology-aided education from the perspective of instructors. Some of the benefits include faster instructional delivery, progressive research, and personal development. The proposed study will attempt to build on these benefits as part of the stakeholder perspective analysis. Therefore, to address this research question, the following hypotheses were created:

• H44: The level of acceptance of technology-aided education by instructors is certain.
• H04: The level of acceptance of technology-aided education by instructors is not certain.

Since instructors are the custodians of technology-aided education, it is important to establish their level of preparedness and acceptance. Therefore, it is necessary to confirm the skill level since the entire process of integrating technology in education revolves around the activities of instructors. Thus, this hypothesis will establish the contribution of instructors in making technology-aided learning effective or otherwise.

The four hypotheses formulated will provide the basis for examining the research scope. Specifically, these hypotheses capture all the variables of the study and put them into perspective. For instance, the first and second hypotheses will assist in relating the background information to the research question. These hypotheses are representative of the different aspects of technology-aided education.

The last two hypotheses are angled on establishing the second part of the study, that is, the stakeholder perspective on the research topic. The third and the fourth hypotheses capture the perspective of learners and educators, who are the beneficiaries of technology-based education. Therefore, as captured in table 5, the creation of the two categories of the hypothesis will ensure that the researcher analyses technology application and stakeholders’ perspectives to make the outcome comprehensive.

Table 5. Perspectives captured by the research hypotheses.

Research Plan

Given that the four research problems have a similar scope, the researcher will use a similar research design. Since the proposed research is subjective, dynamic, and focused, the researcher intends to use qualitative analysis because of its flexibility and ability to accommodate a series of data transcription tools. Moreover, this approach is known to have a margin of error. The researcher will integrate the Google docs software (Miller et al. 2013) in data gathering since it provides room for modification and further scrutiny [26].

The interviews recorded and filled questionnaires will then be subjected to systematic transcription to identify any trend and isolate the responses according to different research problems. For instance, the research will aim at identifying the diverging and converging views for further treatment.

The data collection process will be carried out while observing a series of scientifically approved steps to guarantee respondent privacy. Therefore, each interview session will be accompanied by a consent letter seeking directed permission from potential respondents. According to Newhouse, Williams, and Pearson (2006), the letter will also assure the respondents of their privacy [27]. In addition, the informed consent letter will explain the scope of participation, responsibilities, rights, freedom to decline or respond, and potential benefits of the process.

The interviews will be organized for participants who can spare 15 minutes of their time whole questionnaires will be dropped to busy respondents. The interviews and questionnaires are to be done in the English language because the potential respondents have a good mastery of English as either second or first language. According to Denscombe (2015), the choice of this language is informed by the need to avoid any risk associated with the language barrier in conducting a study [17].

In general, the researcher will target 100 respondents. The sample size will be divided into learner and instructor participants with an equal representational number. I would propose the following sampling formula to generate the sample space that is within the acceptable degree of freedom limit.

n=N/ (1+N (e²))

Where:

n = sample size

N= Target population

e= Degree of freedom

n=100/ (1+100*0.05²)

n=100/1.075

n= 87.907

The data analysis step after collection and transcription will be done through the SPSS package to perform a comparative review of the research problems and generate a cross-tabular representation of the findings. The dependent and independent variables will be quantified through correlation analysis with the aid of tables, charts, and appropriate figures. Other instruments proposed for data decoding include the analysis of variance (ANOVA).

According to Blaxter, Hughes, and Malcolm (2013), the analysis of variance instrument focuses on establishing the mean differences in the set of data collected through disintegrated variation in the sets [8]. The study will endeavor to apply variance analysis to quantify any statistical differences between the data set means as summarised in the formula below.

The confidence interval for the proposed study will be estimated at 99%.

Sample statistic + Z value * standard error / √n

b₁ = 7.1175 ± 2.57 * 0.9631 / √133

= 7.1175 ± 2.57 * 0.9631 / 11.5326

= 7.1175 ±0.2146

= 6.9029 ≤ b₁ ≤ 7.3321

At 95%

b₁ = 7.1175 ± 1.96 * 0.9631 / √133

= 7.1175 ± 1.96 * 0.9631 / 11.5326

= 7.1175 ± 0.1635

= 6.954 ≤ b₁ ≤ 7.281

At 90%

b₁ = 7.1175 ± 1.64 * 0.9631 / √133

= 7.1175 ± 1.64 * 0.9631 / 11.5326

= 7.1175 ± 0.1368

= 6.981 ≤ b₁ ≤ 7.254

Based on the above calculations, the estimated confidential interval is at 6.981 ≤ b₁ ≤ 7.254 of 90%, 6.954 ≤ b₁ ≤ 7.281 of 95%, and 6.9029 ≤ b₁ ≤ 7.3321 of 99%. This is an indication that the estimated confidential interval increases as each level of interval decreases. According to Bakhurst (2009), the application of the ANOVA is focused on quantifying the existing variance in different sets of data by disintegrating the differences existing in the sets for each transcribed group [5]. Therefore, in the proposed research, according to De-George (2013), the ANOVA analysis the means differences of data sets for each research problem [15]. The first element to be computed is the variance between the mean of each problem and the mean of the respondents, which is denoted by (xi -x)². The second element (xij – xi)² will calculate the variance between the results of each research problem.

The proposed study will be concentrated in one region and target specific respondent groups consisting of the educators and learners to relate the objectives to the research questions. Thus, the scope of this study will encompass an examination of the research magnitude from the results addressing each research problem. As captured in chart 1, the research plan will involve proactive modification of the research proposal, expanding the literature review to cover any recent development that can be related to the study, and design of an effective conceptual framework.

The framework will help to define the dependent and independent variables with the objectives and research questions. The fourth activity will be data collection followed by actual data analysis to make sense of the data gathered. The research will then create a draft for relating the literature review to research objectives and the findings. The last part will be an interpretation of the results to draw an inference between the objectives and questions.

Future Work

The literature review suggests that the educational benefits of utilizing mobile devices can be achieved if detailed instructional designs are developed. This will enhance proper modification of learning/teaching scenarios, enhance experimental design quality in mobile intervention, and empower educational practitioners through mobile technology. Moreover, as captured in table 6, it will create a system for isolating impacts and applications to avoid generalization. This means that the experimental design will cover intervention strategies as independent variables that are examined differently.

Avolio (2010) notes that results from such a process will not only be overreaching but also relevant to the research topic [4]. The proposed future research is the isolation of each research problem and performing a comprehensive analysis. Unlike our plan, which consists of four problems, there are very many variables to be considered. Their coverage might not provide an explicit preview of each item of the study, which is categorized into groups.

Table 6. Future research.

Conclusion

In this report, we have summarized the principal contents of the paper is a revised and easier form along with positive sides as well as the critique of the paper. We have explained in detail the process that the authors employed in data collection to obtain relevant information that suited their topic of study. This included the stages involved in collecting articles for review and narrowing them down to the relevant ones. In particular, we have explained how the data was analyzed.

This was done through the use of various mathematical formulas employed in the paper. For instance, Cohen’s d formula used in calculating the effect sizes of the study, and a Comprehensive Meta-Analysis formula are relevant in the creation of the research framework and data analysis. Finally, we have suggested several mechanisms that can be employed in the paper to enhance the easy understanding of its contents. These mechanisms are highlighted in the form of four items. For each item, null and alternative hypotheses are created to relate the research problems to current literature.

Reference List

Ahmed, S & Parsons, D 2013, ‘Abductive science inquiry using mobile devices in the classroom’, Computers & Education, vol. 19, no. 63, pp. 62-72.

Andreadis, N 2009, ‘Learning and organizational effectiveness: a systems perspective performance’, Improvement, vol. 48, no. 1, pp. 5-11.

Ary, D, Jacobs, C & Razavieh A 2012, Introduction to research in education, 6thedn, Wadsworth, Belmont.

Avolio, J 2010, Full range education development, SAGE Publications, New York, NY.

Bakhurst, D 2009, ‘Reflections on activity theory’, Educational Review, vol. 61, no. 2, pp. 197-210.

Bebell, D & Kay, R 2010, ‘One to one computing: a summary of the quantitative results from the Berkshire wireless learning initiative’, The Journal of Technology, Learning, and Assessment, vol. 5, no. 9, pp. 1-60.

Best, J & Kahn J 1998, Research in education, 8th and, Allyn and Bacon, Boston, MA.

Blaxter, L, Hughes, C & Malcolm, T 2013, How to research, Open University Press, Berkshire.

Bruce-Low, S, Burnet, S, Arber, K, Price, D, Webster, L & Stopforth, M 2013, Interactive mobile learning: a pilot study of a new approach for sport science and medical undergraduate students’, Advances in Physiology Education, vol. 14, no. 37, pp. 292-297.

Chaiprasurt, C & Esichaikul, V 2013, ‘Enhancing motivation in online courses with mobile communication tool support: a comparative study’, The International Review of Research in Open and Distance Learning, vol. 9, no. 14, pp. 377-401.

Chauhan, S 2016, ‘A meta-analysis of the impact of technology on learning effectiveness of elementary students’, Computers & Education, vol. 105, no. 3, pp. 14-30.

Chen, M, Tan, C & Lo, B 2013, ‘Facilitating English-language learners’ oral reading fluency with digital pen technology’, Interactive Learning Environments, vol. 5, no. 12, pp. 1-23.

Chiu, L & Liu, G 2013, ‘Effects of printed, pocket electronic, and online dictionaries on high school students English vocabulary retention’, The Asia-Pacific Education Researcher, vol. 22, no. 13, pp. 619-634.

Cohen, J 1988, Statistical power analysis for the behavioral sciences, 2nd edn, Erlbaum, Hillsdale.

De-George, R 2013, Business ethics, Pearson Education Limited, New York, NY.

De-Joodea, E, Van-Heugtena, M, Verheya, F & Van-Boxtela, M 2013, ‘Effectiveness of an electronic cognitive aid in patients with acquired brain injury: a multicentrerandomised parallel-group study’, Neuropsychological Rehabilitation: An International Journal, vol. 23, no. 19, pp. 133-156.

Denscombe, M 2015, Ethics: Ground rules for good research, Open University, Buckingham.

Edwards, M, Rule, A & Boody, R 2013, ‘Comparison of face-to-face and online mathematics learning of sixth graders’, Computers in Mathematics and Science Teaching, vol. 24, no. 32, pp. 25-47.

Fernandez-Lopez, A, Rodriguez-Fortiz, MJ, Rodriguez-Almendros, ML, & Martinez-Segura, MJ, 2013, ‘Mobile learning technology based on IOS devices to support students with special education needs’, Computers & Education, vol. 61, pp. 77-90.

Fleischer, H 2012, ‘What is our current understanding of one-to-one computer projects: a systematic narrative research review’, Educational Research Review, vol. 7, no. 11, pp. 107-122.

Frohberg, D, Goth, C & Schwabe, G 2009, ‘Mobile learning projects a critical analysis of the state of the art’, Journal of Computer Assisted Learning, vol. 25, no. 19, pp. 307-331.

Heflin, H, Shewmaker, J & Nguyen, J 2017, ‘Impact of mobile technology on student attitudes, engagement, and learning’, Computers & Education, vol. 13, no. 107, pp. 91-99.

Hwang, G & Tsai, C 2011, ‘Research trends in mobile and ubiquitous learning: a review of publications in selected journals from 2001 to 2010’, British Journal of Educational Technology, vol. 42, no. 8, pp. 65-70.

Hwang, J, Chu, C, Lin, Y & Tsai, C 2011, ‘A knowledge acquisition approach to developing Mind tools for organizing and sharing differentiating knowledge in a ubiquitous learning environment’, Computers & Education, vol. 6, no. 57, pp. 368-1377.

Lipshitz, R, Friedman, J & Popper, M 2014, Demystifying organizational learning, Thousand Oaks, CA.

Miller, T, Mauthner, M, Birch, M & Jessop, J 2013, Ethics in qualitative research, SAGE Publications Limited, London.

Newhouse, C, Williams, P & Pearson, J 2006, ‘Supporting mobile education for pre-service teachers’, Australasian Journal of Educational Technology, vol. 22,no. 19, pp. 289-311.

Penuel, W 2006, ‘Implementation and effects of 1:1 computing initiatives: a research synthesis’, Journal of Research on Technology in Education, vol. 4, no. 38, pp. 329-348.

Riconscente, M 2013, ‘Results from a controlled study of the iPad fractions game motion math’, Games and Culture, vol. 8, no. 11, pp. 186-214.

Rosenthal, R 1979, ‘The file drawer problem and tolerance for null results’, Psychological Bulletin, vol. 11, no. 86, pp. 638-641.

Runyan, J, Steenbergh, A, Bainbridge, C, Daugherty, D, Oke, L & Fry, B 2013, ‘A smartphone ecological momentary assessment/intervention “App” for collecting real-time data and promoting self-awareness’, PLoS ONE, vol. 8, no. 18, pp. 713-725.

Sung, Y, Chang, K & Liu, T 2015, ‘The effects of integrating mobile devices with teaching and learning on student learning performance: a metal-analysis and research synthesis’, Computer & Education, vol. 94, pp. 252-275.

Van-der-Kleij, F, Feskens, R & Eggen, T 2015, ‘Effects of feedback in a computer-based learning environment on students’ learning outcomes: a meta-analysis’, Review of Educational Research, vol. 85, no. 4, pp. 1-37.

Wang, L & Wu, C 2011, ‘Application of context-aware and personalized recommendation to implement an adaptive ubiquitous learning system’, Expert Systems with Applications, vol. 38, no. 9, pp. 10831-10838.

Warschauer, M, Zheng, B, Niiya, M, Cotten, S & Farkas, G 2014, ‘Balancing the one-to-one equation: equity and access in three laptop programs’, Equity & Excellence in Education, vol. 9, no. 47, pp. 46-62.

Wong, H & Looi, C 2011, ‘What seams do we remove in mobile assisted seamless learning? A critical review of the literature’, Computers & Education, vol. 57, no. 15, pp. 2364-2381.

Wouters, P, van-Nimwegen, C, van-Oostendorp, H & van-der-Spek, D 2013, ‘A meta-analysis of the cognitive and motivational effects of serious games’, Journal of Educational Psychology, vol. 105, no. 2, pp. 249-265.

Yang, Y, Zhang, L, Zeng, J, Pang, X, Lai, F & Rozelle, S 2013, ‘Computers and the academic performance of elementary school-aged girls in China’s poor Communities’, Computers & Education, vol. 8, no. 60, pp. 335-346.

Zhang, J, Sung, Y, Hou, H & Chang, K 2014, ‘The development and evaluation of an augmented reality-based armillary sphere for astronomical observation instruction’, Computers & Education, vol. 19, no. 73, pp. 178-188.

Zucker, A & Light, D 2009, ‘Laptop programs for students’, Science, vol. 6, no. 323, pp. 82-85.

Introduction

Propeller-driven aircraft is more efficacious at low speeds than jet-driven aircraft, for they create higher propulsive efficiency and, consequently, greater thrust while the craft is moving at lower airspeed; however, jet-driven aircraft experience the deficiency of thrust when the craft is moving at low airspeed (Dole & Lewis, 2000, p. 207). Also, the efficiency of propeller-driven craft is higher compared to that of jet-driven craft at lower altitudes (Dole & Lewis, 2000). On the other hand, jet-driven aircraft are more effective at higher altitudes because less fuel is used (Dole & Lewis, 2000, p. 109). In addition, it is better to cruise at higher speeds at high altitudes due to the reduced drag, which also gives an advantage to jet-driven craft at greater altitudes.

Consequently, when choosing the power plant type, it is needed to consider the desired speed and altitude of the aircraft. For cargo and passenger craft that are not large, and where airspeed is not paramount, propellers are often better, especially if the ranges they are to travel are not long (so they do not need to fly long ranges at high altitudes). For military craft (which need to fly faster and require greater thrust), long-distance cargo and passenger craft (which would fly at higher altitudes for a long time), and large aircraft (which would also fly at higher altitudes to reduce the drag), jets are often better (Dole & Lewis, 2000).

Comparing Various Jet-Range Profiles

Which jet-range profile is best depends on what is needed in a particular situation.

· While maintaining a constant Mach and a constant cruising altitude, usually an aircraft utilizes a large amount of fuel to fly given distances which are not long. So, this mode is best for flying short, set distances.

· For a craft to maintain constant thrust and a constant cruising altitude, it is needed to use fuel at a steady rate to keep the thrust at the same level, and, consequently, to maintain the given altitude. However, it should be noted that throttle settings will need to be adjusted to maintain the needed level of trust, for the actual thrust will change due to the loss of weight resulting from the fuel burn (Dole & Lewis, 2000).

· While flying at constant cruising altitude and lowering Mach, it is needed to decrease the fuel consumption to reduce airspeed (Dole & Lewis, 2000). This is probably the best profile to utilize when it is required to maintain constant altitude while flying long ranges, for decreasing the fuel use will lead to a greater specific range (Dole & Lewis, 2000, p. 110).

· When flying at constant Mach while increasing the altitude in the process (cruise-climb technique), it is possible to achieve an improvement in range thanks to the decrease in weight of the craft and the lower density and temperature at high altitudes; thus, this is the best profile to use when it is permitted to increase the altitude (Dole & Lewis, 2000, pp. 111-112).

Aircraft Design Features Affecting Takeoff and Landing Performance

There are several characteristics of aircraft design that affect takeoff and landing performance, some of which are:

• Gross weight of the aircraft: greater weight increases liftoff speed and decreases acceleration; so, greater weight increases the takeoff distance. Weight change needs to be taken into account when landing; heavier craft need greater approach speed, and, therefore, longer runways (Civil Aviation Authority of New Zealand [CAA], 2011);
• The features of the wheel (the wheel bearing friction, the drag resulting from braking, the deformation of the tire, the tire pressure, etc.) (CAA, 2011; “Takeoff & Landing Performance,” n.d.);
• Wing peculiarities (e.g., flap settings, wing surface, airfoil, etc.) (CAA, 2011).

As for B-17, there were a variety of subtypes of that craft; some of them utilized the NACA 0018 wind design (Current, n.d.). Different models of B-17 could have a gross weight of nearly 40,260-56,000 lbs (“Boeing B-17 Performance,” n.d.).

References

Boeing B-17 performance. (n.d.). Web.

Civil Aviation Authority of New Zealand. (2011). Takeoff and landing performance. Web.

Current, J. D. (n.d.). American warplanes of WWII. Web.

Dole, C. E., & Lewis, J. E. (2000). Flight theory and aerodynamics: A practical guide for operational safety (2nd ed.). New York, NY: John Wiley & Sons.

Takeoff & landing performance. (n.d.). Web.

Abstract

Caffeine is widely perceived as an energetic stimulus and is highly consumed by many individuals. The effects of this substance can be present in different physical, psychological and behavioural functions and can influence athletic performance. The analysis of previous literature shows that it is crucial to consider the aspect of habituation to coffee among sportspeople, which can alter the impact. Consequently, the proposed research topic is the investigation of caffeine’s effect on physical and cognitive performance among athletes who are not used to the continuous intake of this element. The study will utilise a purposive sampling method and will use a mixed research technique.

Introduction

Coffee is one of the most popular drinks, and many individuals do not imagine mornings without this drink to feel fresher and more active. Coffee contains high levels of caffeine and is perceived to be a stimulus to boost energy and fight tiredness or sleepiness. Professional sportspeople also fall under the category of those who consume this product. The point is that caffeine is “an ergogenic aid” that was proved “to enhance performance across a wide range of capacities through a variety of mechanisms” (Pickering and Kiely, 2018). Consequently, this substance becomes popular among communities and among athletes as an instrument to increase energy levels. Thus, the issue of sportspersons taking caffeine is an issue that imposes a question of its influence on their physical and cognitive performance. This topic is crucial to investigate because it can offer new insights on the problem, identify the trends and determine whether taking caffeine is a useful measure for sports professionals.

Literature Review

It is essential to understand how caffeine (CAF) works and what are the allowed norms for the athletes to avoid potential side effects or negative impact. The discussed substance is present not only in such drinks as coffee and tea, but also in particular foods, like cacao beans, and it produces the results through blocking adenosine receptors (McLellan et al., 2016). Hence, different ways of caffeine consumption are available to athletes, which expands its attractiveness. This product influences the central nervous system and is similar to neuromodulator, which causes a reaction in physical and cognitive functioning (McLellan et al., 2016). Still, the significance of appropriate doses should not be underestimated. An acceptable intake of caffeine should not exceed 200 mg to improve such metrics as “time-to-exhaustion, time-trial, muscle strength and endurance, and high-intensity sprints” ((McLellan et al., 2016:296). Therefore, the athletes should carefully consider the doses and remember that exceeding the advised amount might, on the contrary, deter their results.

The paper has already mentioned the issue of potential CAF’s effect on physical and cognitive performance. Shabir et al. conducted a review of seventeen studies related to the investigation of caffeine oral consumption connection to the changes in particular factors among athletes, such as endurance capacity, memory, motivation, and others. The scholars revealed that thirteen of the studies concluded the presence of CAF’s influence on sportspeople in different directions and tied it to a placebo effect (Shabir et al., 2018). It is curious to notice that the placebo effect can play a significant role in further performance based on their expectations. For instance, those who have positive outlooks proved to feel more alert, while those with negative beliefs about caffeine were more tensed (Shabir et al., 2018). Consequently, differences in perceptions might cause various outcomes in the performance, which implies that those who hold a neutral position can experience more significant effects and responsiveness to CAF.

At this point, it is essential to look at caffeine’s impact on cognitive performance that also plays a vital role in athletics results. One study suggested that CAF ingestion outcome produces a faster response in comparison to placebo condition “at sixty minutes post-ingestion compared to post-exercise” (Duncan et al., 2018:107). Thus, it is possible to say that this substance consumption enhances cognitive performance at higher rates than the perceived expectancies. Moreover, another finding showed that caffeine influenced time interaction in the congruent condition and response accuracy compared to placebo condition, implying that it is “an attentional time enhancer” (Duncan et al., 2018:109). It implicates that CAF positively affects cognitive performance among athletes and can be used as a booster under particular conditions.

The next aspect is the influence of caffeine on physical abilities through investigating the results of cycling time trial and VO2 max in the article of Pickering and Kiely. The outcomes portrayed that among those athletes used to habitual CAF intake, the substance ingestion did not produce any results or ergogenic potential (Pickering and Kiely, 2018). One can say that sportspersons who continuously consume moderate to high doses of caffeine are not subjected to the impact on physical performance. Besides, higher CAF doses might even increase the risk of side effects, “such as tremor, insomnia and increased heart rate” (Pickering and Kiely, 2018:837). Therefore, it is possible to state that habituation lowers the possibility of positive effects. Still, the athletes who were asked to abstain from caffeine for a couple of days produced boosted time-trial performance after having a low CAF dose (Pickering and Kiely, 2018). It shows that professionals who do not consume caffeine daily might experience a positive influence of the substance on physical abilities.

Research Question

Based on the literature review, one can say that caffeine implies specific effects on different aspects of mental and bodily capabilities, which can be reached by placebo condition in particular cases. Thus, the research question is what is the impact of CAF in comparison to given placebo on cognitive and physical performance among athletes who do not have habituation to consume the substance.

Methodology

The research will utilise the combination of qualitative and quantitative methods to answer the question and generate a coherent analysis. The participants of the study will be limited to male football players who represent a substantial cohort among professional athletes. The study will use non-probability sampling because it is cost and time effective, and will recruit the participants based on the purposive method. In such a way, the researcher will search for male footballers willing to participate in the study, and the ones who do not have a habit of CAF intake will be selected. Consequently, the investigation will be narrowed down to a specific group of participants, not based on a random sample, to withdraw the conclusions relative to the topic.

During the quantitative part of the research, it will be required to measure the proportion of participants who experienced the improvement of physical ability and, separately, the enhancement of cognitive performance. Thus, independent variables will be CAF doses and the amount of placebo given to the chosen partakers. The dependent variable in the study will be the results that the football players portray because they might vary individually. The qualitative part will rely on the previous studies in this area and on Lewin’s Field theory. The model assumes that “behaviour is a consequence of the totality of the situation” and that “the dynamic field has more influence on behaviour than past experience or future desires” (Brand and Ekkekakis, 2017:49). Consequently, the researcher will analyse the findings and compare or link them to other secondary sources.

The use of a mixed-method can help to generate more significant and precise results of the study and avoid uncertainty and ambiguity. Statistical software SPSS will be adopted to evaluate the quantitative part of the research, while a thorough investigation of secondary literature and proposed theory will constitute the qualitative part. Hence, the researcher will aim to reach accurate results through precise assessment and utilisation of different resources.

Reference List

1. Brand, R. and Ekkekakis, P. (2018) ‘Affective–reflective theory of physical inactivity and exercise.’ German Journal of Exercise and Sport Research, 48(1) pp.48-58.
2. Duncan, M.J., Dobell, A.P., Caygill, C.L., Eyre, E. and Tallis, J. (2018) ‘The effect of acute caffeine ingestion on upper body anaerobic exercise and cognitive performance.’ European Journal of Sport Science, 19(1) pp.103-111.
3. McLellan, T.M., Caldwell, J.A. and Lieberman, H.R. (2016) ‘A review of caffeine’s effects on cognitive, physical and occupational performance.’ Neuroscience & Biobehavioral Reviews, 71 pp.294-312.
4. Pickering, C. and Kiely, J. (2018) ‘What should we do about habitual caffeine use in athletes?’ Sports Medicine, 49(6) pp.833-842.
5. Shabir, A., Hooton, A., Tallis, J. and F Higgins, M. (2018) ‘The influence of caffeine expectancies on sport, exercise, and cognitive performance.’ Nutrients, 10(10) pp.1528-1529.

Introduction

Telecommuting, commonly referred to as teleworking, is a phenomenon whereby employees have to attend to their duties while away from their offices and submit feedback on work progress through virtual platforms such as the internet. Since COVID-19 was declared a global pandemic, many large firms have been compelled to restructure their daily operations. Managers have had to adopt measures that would adhere to the World Health Organization conventions regarding social distancing and among them was the mandatory work from home policy.

Companies blended this approach on the basis that it would reduce overhead expenses while at the same time limiting workers’ chances of exposure to the virus. Managers have quickly formulated telecommuting policies, delegating different roles and responsibilities to workers alongside the required time limits (Abilash & Siju, 2021). An exploration of the impacts of telecommuting and whether it influences workers’ efficiency, satisfaction, and commitment form the basis of discussion for this paper.

Positive Impacts

In the wake of modern technological advancements, many online platforms can effectively facilitate the work from home policy. The technique blends these modalities to ensure that workers from marginalized areas can perform their office responsibilities while guaranteeing their health safety. In that regard, managers are able to assess and supervise many employees simultaneously compared to the typical landscape office layout (Karácsony, 2021). Concurrently, managers can tap into the skills and knowledge of more qualified personnel who may not be willing and able to work from the firm’s premises. In most cases, such specialists have tight schedules and may not be physically present when needed. Telecommuting helps to solve these challenges by bridging the distance barrier to ensure that the services required by the firm are delivered on time.

According to Karácsony, the technique is a crucial component in promoting cohesion among workers. They are placed in interdependent cohorts and work together despite their different geographical localities. In addition, they are able to strengthen family ties and relationships since they spend most of the time at home. Lastly, companies have reported a significant decline in operational costs. Indirect costs associated with power supply, office equipment repair, maintenance, and budgetary food allocations have been significantly reduced. Although telecommuting faced negligible criticism from employees at its inception, the challenges associated with this technique cannot be overlooked. Some of the unfavorable implications of this approach are highlighted in the section below.

Negative Impacts

It is equiprobable that teleworking can have negative effects on the firm, primarily when the latter does not assess employees’ new working environment. For instance, workers who live in noisy neighborhoods may not deliver quality services due to noise-related distractions. In the long run, this affects their productivity and the performance of the firm. However, they may consider traveling or relocating to working-friendly areas, but this would be uneconomical since they will have to incur additional costs.

Similarly, workers’ concentration may be significantly affected in case of family issues during work hours at home. The minimal supervision can easily make them shift their focus from work to the topic at hand for an unspecified period. Some employees can take advantage of the limited supervision, become lazy, and rush to complete the assigned task haphazardly when the deadlines are almost due (Onyemaechi, Chinyere & Emmanuel, 2018). As a result, their output is negatively affected, restricting the company’s efficient operation. Lastly, the relationship between job satisfaction and telecommuting is not infinitely linear. Beyond certain limits, the application of teleworking has negative impacts on the performance of the firm as demonstrated in the last section of this paper.

Effects on Employees’ Commitment to Work and Performance

There are many conceptual frameworks, written literature, and research studies that confirm a positive correlation between teleworking and employee commitment and performance. As cited by Karácsony, telecommuting influences employees’ devotion and morale at work. In his book, Problems and Perspectives in Management, he argues that the technique reduces cases of absenteeism among employees. Pre-pandemic projections speculate that approximately 11.43% of total job hours were lost through workers’ truancy which later dropped to an unprecedented six-point five percent during the telecommuting phase (Karácsony, 2021). Cases of lateness to work are reduced since they do not have to travel to their workplaces. Generally, the technique enables employees to work in a stress-free, conducive environment as there are no disagreements among them; therefore, their commitment to work and performance improves.

Implications on Workers’ Motivation and Job Satisfaction

Even though the fulfillment from the job tends to increase linearly with the adoption of telecommuting, Karácsony argues that the upward trend may eventually flatten. However, most sections of his work support the idea that the relationship between the two variables is directly proportional. Employees feel motivated to work as the approach allows them to take care of their relatives who might be elderly, physically disabled, or infected by the pandemic. The perception of being overstretched by tight schedules at work is offset since they can comfortably strike a balance between the time allocated for attending to their sick relatives and completing office assignments.

Conclusion

Many duties in an organizational context can be executed by incorporating the teleworking approach. These tasks include but are not limited to preparing account statements, completing clients’ orders, advertising, and branding, among other tasks requiring less attention and concentration span. As illustrated throughout this paperwork, the agility associated with the new work schedules improves workers’ performance, thus accruing benefits to employers and employees. The rubric ensures that companies maintain their everyday operations and serve their clients despite the prevailing crisis.

On the other hand, employees retain their careers hence the income they use to sustain themselves and those who depend on them during the economic recession. However, it is vital for managers to closely monitor the application of this model since exceeding a specific limit may lead to decreased job satisfaction. They should be keen enough to detect the points beyond which a curvilinear association between the two parameters begins and formulate measures that would act as perfect telecommuting alternatives.

References

Abilash, K. M., & Siju, N. M. (2021). Telecommuting: an empirical study on job performance, job satisfaction and employee’s commitment during pandemic circumstances. Management, 8(1), 3547-3560.

Karácsony, P. (2021). Impact of teleworking on job satisfaction among Slovakian employees in the era of COVID-19. Problems and Perspectives in Management, 19(3), 1.

Onyemaechi, U., Chinyere, U. P., & Emmanuel, U. (2018). Impact of telecommuting on employees’ performance. Journal of Economics and Management Sciences, p54-p54.