N ARRATIVE P ERSUASION
5.2. Is Mobile Learning Effective? A Review of Previous App Interventions
(believing that using a system would enhance job performance) and perceived ease-of-use (believing than using a system would not need an effort). This model has been commonly used for studying the adoption of information system in educational and non-educational contexts (Sánchez-Prieto, Olmos-Migueláñez, & García-Peñalvo, 2014) and, consequently, in mobile learning research (Al-Emran, Mezhuyev, & Kamaludin, 2018).
In relation to this concept, mobile (technology) acceptance and mobile application acceptance can be defined as the perception of the ease of use and usefulness of a mobile technology or a mobile application. Previous research has shown that gamification and constructivism content promote technology and mobile acceptance (Baptista & Oliveira, 2017; Elwood, Changchit, & Cutshall, 2006).
Moreover, technology acceptance has been shown to predict the effectiveness of the educational content (Al-hawari & Mouakket, 2010). Consequently, as mobile acceptance predicts the effectiveness of an intervention, and constructivism and gamification predict learning achievements and mobile acceptance, we can assume that mobile learning interventions should follow the basis of constructivism and gamification in order to promote mobile acceptance and, as such, educational outcomes.
5.2. Is Mobile Learning Effective? A Review of Previous App
since they are the most rigorous technique for checking effectiveness. Only through the evaluation of interventions can we evaluate cause-effect relationships and improve future mobile applications. In this sense, researchers in this field usually conduct quasi-experiments, and not experiments, since schools generally insist on using the usual school groups, making random assignment impossible (Ahmed & Parsons, 2013;
F. Martin & Ertzberger, 2013; Sandberg et al., 2011).
In Table 15 we present a review of some experiments (or quasi-experiments) that have checked the effectiveness of educational interventions conducted using mobile applications. Thus, we do not consider other interventions with mobiles devices that have used other tools or features, such as SMS (short message service; Lu, 2008). Moreover, we only include experiments (or quasi-experiments) that use a design with a control group, as absence of such a control group implies that any change in knowledge or achievement will be attributed to the app and the influence of extraneous variables will not be considered (Cheung & Slavin, 2013). Consequently, studies without a control group were excluded from the analyses (Burgess & Murray, 2014; Meilan, Trussell, Gallegos, & Asam, 2015; Teri et al., 2014).
As we can see in the table, 80 percent of the apps were more successful in promoting better learning outcomes than traditional lessons (Ahmed & Parsons, 2013;
Briz-Ponce, Juanes-Méndez, García-Peñalvo, & Pereira, 2016; Jeno, Grytnes, &
Vandvik, 2017; Jou, Lin, & Tsai, 2016; Kiger, Herro, & Prunty, 2012; Ling, Harnish, &
Shehab, 2014; Noguera, Jiménez, & Osuna-Pérez, 2013; Q. Wu, 2015; Yang, Tseng, Liao,
& Liang, 2013; Yoo & Lee, 2015). Moreover, one out of three researchers used mobile learning theories as theoretical background (Briz-Ponce et al., 2016; Kiger et al., 2012;
Nickerson, Rapanta, & Goby, 2017; Sandberg et al., 2011; Yoo & Lee, 2015). Only one study (6% of the total) relies on the constructivist theory (Sandberg et al., 2011), and another on the self-determination theory (Jeno et al., 2017) which, as seen previously, is related to the gamification approach. Nevertheless, 26 percent of the studies do not refer to any theoretical background to support the development or the use of the
mobile application (Crawford et al., 2016; Noguera et al., 2013; Q. Wu, 2015). This is in line with previous reviews that have shown that a number of studies in mobile learning are not grounded in theory (Bano et al., 2018; Y. Park, 2011).
Moreover, 80 percent of the interventions consist of sessions in which students use the mobile applications during class time. In these sessions, students in the experimental group use the mobile application in class, whereas students in the control group follow a classic lesson related, or not, to the educational content of the app (Ahmed & Parsons, 2013; Briz-Ponce et al., 2016; Diliberto-Macaluso & Hughes, 2016; Jeno et al., 2017; Jou et al., 2016; Kiger et al., 2012; Ling et al., 2014; Noguera et al., 2013; Yang et al., 2013; Yoo & Lee, 2015). In the remaining 20 percent, students use the app in an authentic context, whether it is for acquiring fauna and flora knowledge at the park (Crawford et al., 2016) or for learning English vocabulary about animals in the zoo (Sandberg et al., 2011).
Finally, we can conclude that there is no agreement on the duration of the intervention, as 53% of the experiments used just one session (Ahmed & Parsons, 2013;
Briz-Ponce et al., 2016; Jeno et al., 2017; Jou et al., 2016; Ling et al., 2014; F. Martin &
Ertzberger, 2013; Yang et al., 2013), whereas 26% run for several weeks and 6%
delivered as an entire course (Kiger et al., 2012; Nickerson et al., 2017; Sandberg et al., 2011; Yoo & Lee, 2015). At any rate, one session interventions appear to be sufficient for testing the effectiveness of the mobile learning apps.
Considering previous research, we can assume that mobile learning interventions are effective for educational purposes. However, as far as we know, in the case of online risks and online safety, and more specifically, in the case of contact with strangers, only prototypes of apps have been developed, but there have been no experiments to check their effectiveness (Fan, M., Liyue, Y., & Bowler, 2016; Hswen, Rubenzahl, & Bickham, 2014; Singh, Ng, Yap, Husin, & Malim, 2017). Consequently, further research in this area is needed with experiments checking the effectiveness of these tools.
Table 15.
Review of previous app interventions
Study Topic and characteristics of the
intervention Theoretical
background Sample, study design, duration and
measurement Results
(Ahmed &
Parsons, 2013)
Science
ThinknLearn. Four main
components: Knowledge Testing, Learning, Prediction & Selection, and Observation & Measurement.
Abductive Inquiry Model (AIM)
161 students in high school One control (classic class) and one experimental group (app in class) One session
Pre-test and several post-tests:
knowledge in science.
Experimental group gained more knowledge in science.
(Briz- Ponce et al., 2016)
Anatomy
Brain System 3D: This app allows students to learn about the structure and function of the human brain by interacting with high-resolution rotating 3D images in real time.
Mobile learning
30 medical students (18-25 years) One control (classic class) and one experimental group (app in class) One session
Pre-test and post-test: knowledge about anatomy. Content quality, navigation, credibility, design and security and privacy.
The performance of the learners was better using the app as a supportive tool than using the traditional methods.
Study Topic and characteristics of the
intervention Theoretical
background Sample, study design, duration and
measurement Results
(Crawford et al., 2016)
Engagement with nature
Agents of nature: this highlights the flora, fauna, and ecology of the park.
It allows an avatar to be selected which interacts with other cartoon animals. Users can accept challenges associated with different locations in the park.
-
747 children (9-14 years) One day
One control (paper map) and two experimental groups (mobile app and park educator)
Pre-test: Connection to nature.
Post-test: Connection to nature, fun, attitude toward the park and park content knowledge.
There were no differences in the connection to nature, but children who used the app had more fun.
(Diliberto- Macaluso &
Hughes, 2016)
Introduction to psychology Interactive 3-D Brain app: This is interactive and allows the user to rotate the brain and zoom around brain structures in 3D. It also contains learning modules about case studies, cognitive disorders, damage, associated functions and brief abstracts and links to research.
-
54 undergraduate students Three sessions
One control (textbook) and one experimental group (app)
Pre-test and post-test: performance
The increase in performance was significantly greater on the multiple choice and composite measures, but not on labelling, for the app students.
(Jeno et al., 2017)
Identification of species
ArtsApp: This allows students to identify species, contains pictures of the characteristics of the species and textual descriptions, and keeps track of the progress of the student.
Self-
Determination Theory (SDT)
71 biology students (21-22 years) One session
One control (textbook) and one experimental group (app) Post-test: students’ intrinsic motivation, perceived competence, and achievement
App students obtained higher achievement scores, perceived competence, and intrinsic motivation scores.
Study Topic and characteristics of the
intervention Theoretical
background Sample, study design, duration and
measurement Results
(Jou et al., 2016)
Engineering education
IM2Learn: This includes science concepts, test item bank, course database, knowledge database, and user profile database.
Problem-based Learning (PBL)
87 university students One session
One control (nothing) and one experimental group (app) Pre- and post-learning tests, students’ cognitive load, learning attitude and reception.
App students achieved significant
improvements in learning effectiveness and attitude. There were no differences in the cognitive load results.
(Kiger et al., 2012)
Maths
Ten math apps were selected based on several criteria: curriculum alignment, authentic skill practice, operational ease, and attractiveness to students.
Mobile learning
87 students in 3rd grade 9 weeks
One control (classic lesson) and one experimental group (iPod with 10 apps)
Post-test: multiplication.
Students in the experimental condition outperformed the other students on the multiplication test.
(Ling et al., 2014)
Statistical Concepts
Learn-Statistics: This provides real- time and interactive feedback to the user.
An Integrative Conceptual Model of Learning Bloom’s Taxonomy
26 college students (M=20.27 years) One session
One control (classic lesson) and one experimental group (app)
Comprehension quiz score.
The app group out- performed the control group on the
comprehension quiz.
Study Topic and characteristics of the
intervention Theoretical
background Sample, study design, duration and
measurement Results
(F. Martin
&
Ertzberger, 2013)
Art
Lectora Inspire: The art lesson incorporated information on five different paintings. For each painting, the app provided information about the artist, the artwork, the medium and style.
Here and now learning
109 undergraduate students (18-22 years)
One session
One control (computer based instruction CBI) and two
experimental groups (app with iPad, app with iPod)
Pre-test and post-test: knowledge.
Attitude survey.
The CBI treatment scored higher than the iPad and iPod
treatments. The iPad group had the highest attitude scores, whereas the CBI treatment had the lowest scores in the attitude survey.
(Nickerson et al., 2017)
Business communication
Schoology: Students were provided with a series of individual and group tasks to complete online, including discussion forums, digital
storytelling, and video creation tasks.
Mobile learning
113 university students One course
One control (nothing) and two experimental groups (mobile learning and conventional group) Pre-test and post-test: knowledge and comprehension of business communication concepts
There was no difference between conventional and mobile learning approaches.
(Noguera et al., 2013)
Manual therapy
3D mobile application -
76 students of physiotherapy Two practical lesson of 5h each One control (classic lesson) and one experimental group (app)
Pre-test and post-test: anatomical knowledge
The app was more effective than the classic lesson.
Study Topic and characteristics of the
intervention Theoretical
background Sample, study design, duration and
measurement Results
(Q. Wu, 2015)
English vocabulary
Word Learning-CET6: This contains a 1,274 word database and lets the students create sample tests.
-
70 medical school students 55 days
One control (pushing messages to encourage them to study) and one experimental group (app)
English vocabulary test.
The app group remembered more words.
(Sandberg et al., 2011)
English vocabulary
The MEL-application contains five different game types: multiple choice quiz, spelling quiz, memory game, Yes or No game, and
jigsaw puzzle.
Constructivism and mobile learning
75 students (8-10 years) in 5th grade Two weeks
One control group (classic lesson) and two experimental groups (app during a visit to the zoo and app in the visit with participants keeping the app for two weeks)
Pre-test and post-test: mastery of a set of targeted English words.
The participants that kept the app scored significantly higher on post-test than the other conditions. However, if we consider the learning time, there are no differences between conditions.
(Yang et al., 2013)
Chinese poetry
Ubiquitous Poetry Learning Scheme includes: presentation of poem content, annotations, explanation, and multimedia resources.
Multimedia learning
64 students in 7th grade One session
One control (textbook) and one experimental group (app) Pre-test: existing knowledge of Chinese poetry. Post-test: learning achievements
Learning by using UPLS is more effective than conventional learning in promoting learning achievement of the students.
Study Topic and characteristics of the
intervention Theoretical
background Sample, study design, duration and
measurement Results
(Yoo & Lee, 2015)
Cardio-pulmonary assessment
iStethoscope Expert Mobile learning
22 nursing students Five weeks
One control (human patient simulator) and one experimental group (app)
Pre- and post-assessment. Student satisfaction with their education.
The app group was only significantly higher on the post-test of knowledge of lung assessment.