The Effects of Integrating Mobile Devices With Teaching and Learning on Students’ Learning Performance Research Paper

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 and are mean scores while and are sample sizes. The and 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;

ESPre/Post Test Two Groups = (X1 Post – X1 Pre) – (X2 Post – X2 Pre) / SDPost

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 SDPost was computed as follows:

SDPost= (n2Post – 1)s22Post + (n1 Post – 1) s21Post/ (n2Post + n1 Post-2)

Where n1 Post and n2Post are experimental and control group sample sizes. The s21Post and s22Post 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

. The second element 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.

Chart.1. Research timeline.

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.

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