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Universal Access in the Information Society

, Volume 17, Issue 2, pp 325–334 | Cite as

An analysis of the influence of a mobile learning application on the learning outcomes of higher education students

  • Aijaz Ahmed Arain
  • Zahid Hussain
  • Wajid H. Rizvi
  • Muhammad Saleem Vighio
Long Paper

Abstract

This study investigated the influence of a mobile learning (M-Learning) application on the learning outcomes of university students. The learning outcomes were assessed in terms of secured score in the Communication Skills course using the App for the period of one semester. The M-Learning App was developed for university students to make learning possible from anywhere, at anytime, and through any smartphone. An experiment was conducted to measure the learning outcomes of the students. In each group (experimental and control), 106 students were randomly selected using SPSS random sample cases. The learning outcomes were measured by means of a standard test designed by three course experts. Both groups took the test at the start of the semester; the results were recorded as pre-test. However, both groups undertook the same test again at the end of the semester as a post-test; this time the questions were shuffled. The results of the experiment revealed that there is statistically significant difference between the experimental and control groups in their post-test results. The experimental group secured higher score in the post-test as compared to the control group. The findings of this study suggest that the App has positive influence on the learning outcomes of the students.

Keywords

Universal accessibility M-Learning Experimental design Learning outcomes 

1 Introduction

Widespread use of smartphones has provided a unique opportunity for better learning experiences. Mobile devices such as PDAs, tablet-PCs, and mobile phones (including smartphones) are being used at increasing pace in the academic world, particularly in higher education institutions [1, 2, 3]. Similarly, the use of M-Learning is on the rise in educational institutions [1]. The rapid growth of mobile technologies has provided learners with great opportunities to learn inside as well as outside the classrooms [2, 4]. The use of mobile Apps for universal access to online learning and education could provide a wealth of knowledge to researchers, instructors and educators who plan to utilize M-Learning for their learners [5]. Researchers have pointed out that mobile devices are essential elements for learning at higher education institutions [6] stressing that M-Learning means learning through any mobile device taking place in various contexts [7]. The key benefit of M-Learning is its mobility aspect which enables students to exchange information anywhere and at anytime, removing the problem of physical presence of students in the locality of an institute. Thus, M-Learning promotes collaborative learning through students’ interaction [8]. According to Emran and Shaalan [9], M-Learning encourages information sharing between instructor and learner while communicating with each other. M-Learning encourages learning accessibility and flexibility among students and helps in increasing students’ performance and satisfaction on learning materials [10].

From the perspective of an M-Learning App, two factors are essential: usability assessment and learning outcomes of the students after use of the App for a certain period of time. Usability assessment of an App is an important aspect; presumably good usability can enhance user experience and can be linked with better learning outcomes [11]. Usability evaluation of mobile Apps has been gaining extensive attention in the HCI field [12]. For improved M-Learning, Fetaji et al. [13], emphasize to measure the usability of mobile Apps with suitable usability evaluation methods. We have evaluated the usability of this newly developed M-Learning App, and the results have been published in [14]. The research work has also been conducted for measuring learning outcomes of the learners using mobile Apps [15, 16, 17, 18, 19].

Use of M-Learning Apps in higher education and its relationship with learning outcomes can have huge implications for reforming educational policies providing enriched learning experience to students. Recently, in Pakistan 3G/4G technology has been launched. According to a recent report, the annual subscribers of cellular phones in Pakistan have increased to more than 139 million and subscribers for 3G/4G are more than 39 million [20]. It is an urgent need to utilize this technology for improving educational standards in the country. As most of the universities in Pakistan have the necessary infrastructure for universal access of education through the use of ICT tools, this can be the right time for implementing and evaluating an M-Learning system at higher education institutions. We have developed an M-Learning App for university students to support learning anywhere, at anytime and through any smartphone. Keeping this scenario in mind, the focus of this paper is on the following main research question (RQ):
  • RQ: Does the use of the M-Learning App (in addition to traditional classroom learning) enhance learning outcomes of the students?

The research question is further elaborated in the Sect. 3.

1.1 The mobile learning App

The M-Learning App was developed at Quaid-e-Awam University, Nawabshah, Pakistan. The App is accessible through the browser of any device including a desktop computer (PC), laptop, tablet-PC including iPad, any smartphone including iPhone and Windows Mobile based phones. For this study, we have also created a native Android-based mobile App for accessing it on the users’ smartphones. The App consists of the following features: various courses, courses’ lecture-wise videos, notes, MCQ type tests, chat room and forum. The App also records users’ login time and logout time, the number of likes for each video, ratings for each video, total number of times each video is viewed and comments regarding the video by the users. The users have the option to write their own notes for each video separately in their personal accounts. Chat room functionality is available for group chatting and a forum functionality is also available for posting questions to be answered by any of the users.

Figure 1a shows the login screen and 1b the main menu screen where four options are available: courses, chat room, forum and FAQs.
Fig. 1

Snapshots of the developed App a login screen, b main menu

Figure 2a shows lectures of a course with videos, notes and MCQ test of each lecture. Figure 2b shows MCQ test screen.
Fig. 2

Snapshots of the developed App a Lecture-wise videos, notes and MCQ test, b MCQ test screen

In short, this paper is organized into five sections that include related work which is presented in Sect. 2. The methodology of the study is explained in Sect. 3. In Sect. 4, results along with their discussion are provided. Conclusions, implications and future research are finally presented in Sect. 5.

2 Related work

The use of computational devices in the educational sector is increasing day by day [21]. However, because of easy and affordable access to mobile devices, the learning mechanisms have also been shifted from stand-alone computers to mobile devices [22, 23]. Various studies suggest that the use of mobile applications influences learning outcomes [15, 16, 17, 18, 19]. In [15], a mobile App was developed for the first-year university students to assess its influence on learning skills (use of Microsoft PowerPoint and Word). The students took part in the experiment forming one control group and two experimental groups. One of the experimental groups was assisted with computational thinking and ubiquitous learning (the mobile App was provided); another experimental group was assisted only with computational thinking; no other treatment was provided to the control group. The study revealed that the students who were assisted with the mobile App (i.e. ubiquitous learning) had a significantly higher learning ratio compared to those who had no access to the App. Briz-Ponce et al. have studied effects of M-Learning using the App. They have compared the results of 30 university students. They provided an anatomic mobile App to the experimental group, while the control group was taught by conventional face-to-face classroom teaching. According to the results of the study, performance of the experimental group using the mobile App was better than the control group [24]. Furthermore, in [16] a M-Learning App was developed implementing a Five Step Vocabulary Learning (FSVL) to assess the performance of students following English as a second language. In order to find the effects of the App, one teacher and 80 students participated in the study. Based on the use of the App, a questionnaire was designed and distributed among the participants. Further, the data were collected by conducting interviews from the participants. The findings revealed that the mobile application remained very effective to motivate participants towards learning and to improve their performance. In a M-Learning context, Harley et al. [17] conducted a study to compare undergraduate students’ emotions as well as learning outcomes using mobile-augmented reality apps. The research found that the learners in the outdoor study enjoyed more and felt less boredom than the indoor laboratory study. In [18], WhatsApp for mobile devices has been considered for educational purposes. The study was conducted with 80 Spanish university students taking B1 English language course. The students were divided into two groups (experimental and control groups with 40 students in each group) and were given pre-test and post-test questionnaires. The experimental group interacted with the application and the control group did not use the application. The focus of the study was to find out which student group remained better in terms of accuracy when faced with lexical, grammatical and mechanical parameters of the English language. The experimental study revealed that though English was the second language of the students, WhatsApp as a mobile application provided fruitful results. The results of the study show significant difference between the groups: the experimental group outperformed the control group.

In another study presented in [19], WhatsApp was used to support learning and teaching in the university. In this study, it was found that the impact of mobile applications such as WhatsApp on learning and teaching was positive when it comes to the interaction between teachers and the students. Jou et al. carried out a study in which they conducted an experiment to assess the learning outcomes of the university students. They developed the so-called M-Learning App for the study. The study results showed that the App influenced positively the students’ learning performance [25]. Rahimi and Miri have investigated the learning outcomes of the students using a pre-test and post-test quasi-experiment, in which the experimental group used a mobile dictionary installed on their mobile phones while the control group used the same dictionary’s printed version only. The study results revealed that the performance of the experimental group was better than the control group in the post-test [26].

In this research, we have assessed the positive attitude of engineering and science students at the University towards the Communication Skills course; the Communication Skills Attitude Scale (CSAS) [27] was used for the assessment. CSAS has been widely used in medical field [28, 29, 30, 31].

It is evident from the literature review that improving learning skills using mobile Apps is an emerging trend and, thus, needs much attention specifically in the context of developing countries where mobile applications are not used persistently as a norm. Therefore, the focus of this study is to bring some addition to the literature.

3 Methodology

In the present study, the learning outcomes of the students were measured using an experiment. The experiment was conducted in a real learning environment during the semester. In the experiment the mobile App was used as a manipulation to assess if the “mobility” of the course content such as lectures, variety of quizzes and opportunity to engage with fellow students can influence the learning outcomes. Figure 3 shows the flow of the experimental design.
Fig. 3

Experimental design

The target population for the experiment involved all first-year students in Bachelor of Engineering (BE) and Bachelor of Science (BS) 4-year university degree programs who undertook the Communication Skills course in their second semester. It is important to control confounding variables in an experiment. Two important variables, prior knowledge and attitude towards the course were used as possible confounding variables, based on the presumption that learning motivation and involvement stem from prior knowledge and attitude towards the course. The researchers have also emphasized that prior knowledge has positive effects on learning outcomes [32, 33, 34, 35, 36]. Another researcher has highlighted the importance of prior knowledge for enhancing learning outcomes [37]. Positive attitude towards learning enhances learning outcomes [38]. So, both prior knowledge and attitude towards the course were used as possible confounding variables. If prior knowledge of and attitude (positive) towards the course are higher in the experimental group then it will be difficult to isolate the “mobility effect”, so there can be a chance of committing a Type I error. Similarly if prior knowledge and attitude (positive) are higher in the control group then there can be a chance of committing Type II error. Before the manipulation it was ensured that there is no difference between the experimental and control groups in terms of their prior knowledge and attitude towards the course.

At the start of the semester (in the first week), the questionnaire was administered among 397 students during their regular classes. The students were informed about the purpose of the study and were guided how to participate in the study. Approximately 25 min were taken by the students to complete the questionnaire. The 379 students completed the questionnaire while only 18 questionnaires of the students were rejected due to incomplete information. After analyzing the questionnaire, 53 students who did not own smartphones were excluded from the experiment. In addition 14 students who did not own Android smartphones were further excluded from the experiment because the App was Android based, leaving behind 312 students only.

In the second week of the semester, the learning achievement test was conducted. The students were given 20 min to complete the test. This learning achievement test, conducted at the start of the semester, was the pre-test. The purpose of the pre-test was to evaluate whether all students had an equivalent prior knowledge of the course or not. Prior knowledge of the course was considered as possible confounding variable in order to ensure that the respondents equally populated in both experimental and control groups. From the (n = 312) students, finally taking part in the experiment, 106 students were randomly selected through SPSS for the experimental group and 106 students for the control group. Among the students selected for the experiment (n = 212), 190 were male and 22 were female. The randomization of the cases in the groups and monitoring of the control variables helped to ensure homogeneity of the groups. The random selection of the cases across six different departments would enhance viability of the experiment to replicate.

The App was available to the experimental group for use at the beginning of the semester along with the traditional classroom learning, while the control group was only exposed to the traditional classroom learning. We describe traditional classroom learning as when teacher interacts face-to-face with students for delivering instructional material while being physically present in same classroom, as explained in [39, 40, 41].

At the end of the semester, the same learning achievement test (post-test) was conducted by both groups in order to measure and compare their learning outcomes. Various research studies have used the same tests as pre-test and post-test [42, 43, 44, 45]. However, the questions in the post-test were shuffled in the present study by following the technique used in [46].

3.1 Measures

3.1.1 Prior knowledge

Learning outcomes were assessed through a standard MCQ type test weighted and approved by three experts of the course. The test consisted of 20 MCQ questions. All three experts endorsed with census that the test can be used to assess prior knowledge of the course. Prior knowledge used in this study has a specific meaning that relates to the specific content of the course. The MCQ test was designed keeping in mind the content domain, that is why prior knowledge was used as the control variable, to examine if both groups are equally populated in terms of the content knowledge as was done in [24].

3.1.2 Attitude towards the course

Validated scale (CSAS questionnaire) was used to assess attitude towards the Communication Skills course. It was ensured that the attitude towards the course between the experimental and control groups was the same. During analysis independent samples t-test was used to compare the two groups in terms of their attitude towards the course. The CSAS questionnaire was adapted from the questionnaire developed by [27]. Demographic questions made the last part of the CSAS questionnaire for collecting the demographic data of the students, i.e. age, gender, owning a smartphone, etc.

3.1.3 Learning outcomes

The same approved MCQ test was also used to assess the learning outcomes of the students. The learning outcomes were assessed in terms of the specific content understanding. Initial results of the test taken by both groups were recorded as pre-test and the same test was taken again by both groups at the end of the semester which was recorded as post-test as was done in [24]. To assess learning outcomes within the experimental and control groups, a paired samples t-test was conducted. To compare learning outcomes between the experimental and control groups, an independent samples t-test was conducted based on their post-test results.

In order to respond to the main research question of the study, the following hypothesis (H1) was formulated:

H1

There will be a statistically significant difference between the experimental and control groups in their post-test scores (learning outcomes).

4 Results and discussion

Out of 312 eligible students for the experiment, 212 participants were randomly selected through SPSS as follows: 106 students were selected for the experimental group and 106 students were selected for the control group. All 212 participants of the experiment owned Android smartphones and reported to have internet access on their smartphones. All participants were aged between 16 and 20 years. In the experimental group 87.74% of the participants were male and 12.26% were female while in the control group 91.51% of the participants were male and 8.49% participants were female.

Prior positive attitude towards the course and prior knowledge of the course were assessed by using the CSAS questionnaire and the pre-test, respectively. Table 1 shows the results of independent samples t-test for prior positive attitude towards the course and prior knowledge of the course of both experimental and control groups.
Table 1

Independent samples t-test

Grouping variable

Testing variable

t-value

Probability

Experimental/control

Positive attitude

t(210) = 1.486

p = 0.119

Experimental/control

Prior knowledge (pre-test)

t(210) = 0.324

p = 0.746

In Table 1, the results of independent samples t-test for both positive attitude and prior knowledge (pre-test) show that there was no statistically significant difference between the experimental and control groups (P>0.05) in terms of positive attitude towards the Communication Skills course and prior knowledge of the course. Therefore, cases were equally divided in the experimental and control groups in terms of their positive attitude towards the course and their prior knowledge of the course.

Figure 4 shows the mean of positive attitude scores of the students towards the Communication Skills course for both groups, grouped by department. The results showed that the experimental and control groups’ prior positive attitude towards the course was almost equivalent.
Fig. 4

Mean of positive attitude score for both groups, grouped by department

Figure 5 shows the mean of the pre-test results for both groups, grouped by department. The results show that the experimental and control groups’ prior knowledge of the course is almost equivalent.
Fig. 5

Mean of the pre-test results for both groups, grouped by department

4.1 Pre-test and post-test results

Table 2 shows the results of paired samples t-test (pre-test and post-test) of the experimental and control groups.
Table 2

Paired samples t-test

Group

Pre-test mean

Post-test mean

t-value

Probability

Experimental

7.745

16.688

t(105) = −37.36

p = 0.000

Control

7.830

13.745

t(105) = −7.92

p = 0.000

There was a statistically significant (p < 0.001) difference between the pre-test and post-test results of the both experimental and control groups as shown in Table 2. The control group was exposed to traditional classroom learning as mentioned earlier whereas the experimental group was exposed to both traditional classroom learning and the M-Learning App. The results suggest that the learning outcomes were enhanced for both groups in terms of pre-test and post-test results. However, the post-test mean results suggest that the experimental group’s learning outcomes were higher than the control group. It is noteworthy that pre-test and post-test results of the control group were also significant, because they took traditional face-to-face classes and their enhanced learning outcomes can be associated to traditional classroom learning.

Figure 6 shows the mean of pre-test and post-test results of the students for both groups, department-wise. The results show a clear difference between the experimental and control groups’ knowledge of the course at the start of the semester and at the end of the semester, scoring higher in the post-test conducted at the end of the semester. The consistent results across the departments suggest viability of the experimental replication.
Fig. 6

Mean of pre-test and post-test results for both groups, grouped by department

Table 3 shows group statistics of both the experimental and control groups in terms of their post-test results; the results indicate that the experimental group has obtained a higher mean than the control group in their post-test results of the course.
Table 3

Group statistics

 

Group

N

Mean

Std. deviation

Std. error mean

Post-test

Experimental group

106

16.689

1.495

0.145

Control group

106

13.745

2.898

0.282

Table 4 shows independent samples t-test between the experimental and control groups in terms of their post-test results.
Table 4

Independent samples t-test

Grouping variable

Testing variable

t-value

Probability

Experimental/control

Post-test results

t(210) = 9.292

p = 0.000

The results show that there is a statistically significant (p < 0.001) difference between the experimental and control groups in terms of their post-test score. The experimental group obtained higher scores in the post-test. Thus, the results suggest that the exposure of the M-Learning App to the experimental group has contributed in enhancing the learning outcomes of the students. The results are consistent with hypothesis H1: There will be a statistically significant difference between the experimental and control groups in their post-test scores (learning outcomes), as formulated in Sect. 3. The results corroborate previous research findings that M-Learning enhances learning outcomes of the students thus the App can be utilized for M-Learning purpose [15, 16, 17, 18, 19].

We recommend the use of M-Learning Apps to complement traditional classroom learning in order to enhance learning outcomes of university students in similar situations. Tsai et al. [15] and Briz-Ponce et al. [24] also suggest using mobile Apps as an additional tool to complement formal conventional learning methods. Mackey and Ho also recommend to integrate web-based software tools as an additional resource in a blended learning environment [47].

Figure 7 shows the means of both groups’ pre-test and post-test results, grouped by department; it further indicates that the pre-test results of both groups are almost equal. Whereas, there is evident difference in the post-test mean results of both the experimental and control groups.
Fig. 7

Mean of both groups’ pre-test results and mean of both groups’ post-test results

5 Conclusions

The use of advanced technologies is rapidly changing and enriching learning experiences; as a result, this enrichment of experiences influences learning outcomes. There can be various factors that may influence learning outcomes, such as prior course knowledge, attitudes towards the course, learning motivation and learning involvement. A basic premise of this paper was to isolate the “mobility effect” which entails that students can access course content (lectures, a variety of quizzes and the opportunity to engage with class fellows) anywhere, at anytime and through any smartphone; the “mobility effect” would have a positive influence on learning outcomes.

In response to the main research question of this study (“Does the use of the M-Learning App (in addition to traditional classroom learning) enhance learning outcomes of the students?”), the results of the study indicate enhanced learning outcomes of higher education students when they used the M-Learning App along with traditional classroom learning. As the experimental group obtained higher scores in their post-test in comparison to the control group the difference was statistically significant. Thus, the exposure of the M-Learning App to the experimental group has contributed in enhancing the learning outcomes of the students. As the App has enhanced the learning outcomes of the students significantly, it can be utilized for the purpose of M-Learning in the context of higher education institutions. However, it is important to note that the pre-test and post-test results of the control group were also significant as they took traditional face-to-face classes and their enhanced learning outcomes can be associated to traditional classroom learning. Hence, M-Learning Apps can be employed to complement traditional classroom learning.

5.1 Implications and future research

The focus of this study was to isolate the “mobility effect” and its influence on learning outcomes. The interaction between learner and instructor influences learning outcomes. From an instructor’s perspective factors like instructor quality, learning activities and blended instructional design are essential, whereas from a learner’s perspective factors like learning motivation and learning involvement [48], prior knowledge [33, 34, 35, 36, 48] and attitude towards learning [38] are essential. Both prior knowledge and attitude towards a course are specific factors whereas learning involvement and learning motivation are general factors. Since the study conducted targeted a specific course, both prior knowledge and attitude towards the course were used as possible confounding variables, based on the presumption that learning motivation and involvement stem from prior knowledge and attitude towards the course. The factors related to instructors were not the prime focus of this study. However, to limit instructor factors the respondents were randomly selected across different departments. The evidence sought in this experimental study suggests that availability of subject content on mobile devices can influence learning outcomes. In the future, it will be interesting to assess learning outcomes by adding blended instruction design as an additional scenario in an experiment. Moreover, additional variables such as learning motivation, learning involvement and instructor quality can be employed in future studies. The evidence can be further strengthened by providing a desktop-based application to the control group as well; this will further help to isolate the “mobility effect”. It will also be interesting to see if the M-Learning App is useful across different disciplines or different courses.

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Aijaz Ahmed Arain
    • 1
  • Zahid Hussain
    • 1
  • Wajid H. Rizvi
    • 2
  • Muhammad Saleem Vighio
    • 1
  1. 1.Quaid-e-Awam University of Engineering, Science and TechnologyNawabshahPakistan
  2. 2.Institute of Business AdministrationKarachiPakistan

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