Table 1
Demographic information for online survey participants (N = 60).
| DEMOGRAPHIC | FREQUENCY (PERCENT OF RESPONDENTS) | NUMBER | |
|---|---|---|---|
| Gender (N = 60) | Female | 56.66% | 34 |
| Male | 41.67% | 25 | |
| Non-Binary | 1.67% | 1 | |
| Age (N = 60) | 19–21 | 93.33% | 56 |
| Above 21 | 6.67% | 4 | |
| GPA (N = 60) | Lower than 2.0 | 0 | 0 |
| 2.01 ~ 2.49 | 0 | 0 | |
| 2.50 ~ 2.99 | 0 | 0 | |
| 3.00 ~ 3.49 | 13.33% | 8 | |
| 3.50 and above | 86.67% | 52 | |
| Major (N = 60) | Astrophysics | 8.33% | 5 |
| Biochemistry | 8.33% | 5 | |
| Chemistry | 10% | 6 | |
| Communication | 5% | 3 | |
| Economics | 5% | 3 | |
| Math | 16.67% | 10 | |
| Political Science | 5% | 3 | |
| Psychology | 16.67% | 10 | |
| Sociology | 8.33% | 5 | |
| Others | 16.67% | 10 |
Table 2
Demographic Information for Interview Participants.
| PARTICIPANTS | GENDER | AGE | GPA | MAJOR | MOBILE LEARNING EXPERIENCE |
|---|---|---|---|---|---|
| Participant 1 | Female | 19–21 | 3.50 and above | Computer science & philosophy | Learning languages from Duolingo |
| Participant 2 | Female | 19–21 | 3.50 and above | Biology | Learning languages from Duolingo |
| Participant 3 | Female | 19–21 | 3.50 and above | Math | Using Apps required by courses to finish coursework |
| Participant 4 | Female | 19–21 | 3.50 and above | Psychology | Taking courses on smartphones, such as Coursera |
| Participant 5 | Female | 19–21 | 3.50 and above | Psychology | Learning TOEFL from an App for the TOEFL exam |
| Participant 6 | Female | 19–21 | 3.50 and above | Linguistics | Learning extracurricular knowledge on multiple Apps, such as Duolingo |
| Participant 7 | Male | 19–21 | 3.00 ~ 3.49 | Astrophysics | Taking online college-level courses |
| Participant 8 | Female | 19–21 | 3.50 and above | Earth, society, & environmental sustainability | Learning video editing and taking courses required by high school |
| Participant 9 | Female | 19–21 | 3.50 and above | Statistics, & accountancy | Learning math from YouTube App |
| Participant 10 | Female | 19–21 | 3.50 and above | Life sciences | Taking online courses |
| Participant 11 | Female | 19–21 | 3.50 and above | Spanish | Learning languages from Duolingo |
Table 3
Preliminary Codebook based on the OLR Theory (Hung, 2010).
| THEME | DESCRIPTION |
|---|---|
| Computer/Internet self-efficacy | Evaluate learners’ confidence and ability to effectively use computer and internet technologies for online learning. Perception of the ability to use computers and software for online tasks. Perception of the ability to perform internet-related tasks and troubleshoot issues. |
| Self-directed learning | Assess learners’ capacity for self-directed learning, including goal-setting, resource identification, and self-regulation. Independence in planning, monitoring, and evaluating their learning process Ability to adapt time management skills from in-person to online learning. |
| Learner control | Measure the extent to which learners can direct and manage their own online learning experiences. Autonomy in choosing learning objectives, pace, and resources. Ability to focus on learning and minimize distractions in the online environment. |
| Motivation for learning | Examine learners’ motivation, both intrinsic and extrinsic, and its impact on their engagement and persistence in online courses. Intrinsic motivation: The inherent interest in acquiring knowledge and skills. Extrinsic motivation: Performing behaviors for specific rewards, such as grades or prizes. |
| Online communication self-efficacy | Assess learners’ confidence and skills in effectively communicating and collaborating with others in the online learning environment. Proficiency in participating in online discussions and group work. Ability to facilitate meaningful interactions in online courses. |
Table 4
Reliabilities of OLR.
| SCALE | ITEMS | RAFIQUE ET AL. (2021) | CHUNG ET AL. (2020) | PRESENT STUDY |
|---|---|---|---|---|
| Computer/Internet self-efficacy | 3 | .81 | .88 | .82 |
| Self-directed learning | 5 | .76 | .89 | .82 |
| Learner control | 3 | .50 | .84 | .70 |
| Motivation for learning | 4 | .77 | .91 | .81 |
| Online communication self-efficacy | 3 | .75 | .89 | .72 |
[i] Note. The Cronbach’s alpha of LC was .62 before removing LC2, which was not reliable enough for the constructs.
Table 5
Results of quantitative data comparison (group 1 minus group 2)*.
| ITEM | tOF EACH ITEM | t AND p OF DIMENSION | COHEN’S d |
|---|---|---|---|
| CIS1 | –2.54 | t = –3.41 | 0.88 |
| CIS2 | –3.88 | p = .001* | |
| CIS3 | –2.29 | ||
| SDL1 | –3.02 | t = –4.23 | 1.09 |
| SDL2 | –2.43 | ||
| SDL3 | –2.94 | ||
| SDL4 | –3.80 | p < .001* | |
| SDL5 | –2.99 | ||
| MFL1 | –4.40 | t = –4.89 | 1.26 |
| MFL2 | –3.56 | ||
| MFL3 | –5.20 | ||
| MFL4 | –2.14 | p < .001* | |
| OCS1 | –2.40 | t = –3.93 | 1.01 |
| OCS2 | –4.92 | p < .001* | |
| OCS3 | –2.18 | ||
| LC1 | –2.67 | t = –3.62 | 0.93 |
| LC3 | –3.55 | p < .001* |
[i] Note. Group 1 includes participants without any mobile learning experiences and less than 2 hours of weekly mobile learning; Group 2 includes participants with more than 2 hours of weekly mobile learning.
Table 6
Interview Results Grouped by Sub-Category.
| SUB-CATEGORY | FREQUENCY | QUANTITATIVE FINDINGS EXPLAINED |
|---|---|---|
| Access to Related Technologies/Resources | 20 | CSE, ISE, SDL, MFL, OCS |
| Awareness Development | 9 | SDL, LC |
| Getting Acquainted with Learning Technologies | 9 | CSE, OCS |
| App Features | 4 | MFL |
| Motivation for Searching Information | 3 | ISE |
| Learning Environment | 3 | OCS |
| Limit on Access | 3 | LC |
| No Influence | 19 | CSE, ISE, SDL, MFL, OCS, LC |
| Total: 70 |