A review of the motivation theories in learning

Gopalan, Valarmathie; Bakar, Juliana Aida Abu; Zulkifli, Abdul Nasir; Alwi, Asmidah; Mat, Ruzinoor Che

doi:10.1063/1.5005376

Cited by 166 publications

(154 citation statements)

References 39 publications

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“…The intrinsic motivation theory explains motivation in the context of learning [25]. Key factors that influence intrinsic motivation are challenge, curiosity, control, and fantasy [25]. Willpower and positive attitude are required to sustain motivation for learning [25].…”

Section: The Intrinsic Motivation Theorymentioning

confidence: 99%

“…Key factors that influence intrinsic motivation are challenge, curiosity, control, and fantasy [25]. Willpower and positive attitude are required to sustain motivation for learning [25]. Intrinsic motivation can influence students to participate in academic activities without external pressure or the expectation of external rewards [25].…”

Section: The Intrinsic Motivation Theorymentioning

confidence: 99%

“…Willpower and positive attitude are required to sustain motivation for learning [25]. Intrinsic motivation can influence students to participate in academic activities without external pressure or the expectation of external rewards [25]. Participation is influenced based on a desire to experience the fun, challenge, and uniqueness of the academic activity [25].…”

Section: The Intrinsic Motivation Theorymentioning

confidence: 99%

See 2 more Smart Citations

The Impact of an Augmented Reality Application on Learning Motivation of Students

Khan

Johnston

Ophoff

2019

Advances in Human-Computer Interaction

345

176

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The research on augmented reality applications in education is still in an early stage, and there is a lack of research on the effects and implications of augmented reality in the field of education. The purpose of this research was to measure and understand the impact of an augmented reality mobile application on the learning motivation of undergraduate health science students at the University of Cape Town. We extend previous research that looked specifically at the impact of augmented reality technology on student learning motivation. The intrinsic motivation theory was used to explain motivation in the context of learning. The attention, relevance, confidence, and satisfaction (ARCS) model guided the understanding of the impact of augmented reality on student motivation, and the Instructional Materials Motivation Survey was used to design the research instrument. The research examined the differences in student learning motivation before and after using the augmented reality mobile application. A total of 78 participants used the augmented reality mobile application and completed the preusage and postusage questionnaires. The results showed that using an augmented reality mobile application increased the learning motivation of students. The attention, satisfaction, and confidence factors of motivation were increased, and these results were found to be significant. Although the relevance factor showed a decrease it proved to be insignificant.

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Section: The Intrinsic Motivation Theorymentioning

confidence: 99%

Section: The Intrinsic Motivation Theorymentioning

confidence: 99%

Section: The Intrinsic Motivation Theorymentioning

confidence: 99%

See 1 more Smart Citation

The Impact of an Augmented Reality Application on Learning Motivation of Students

Khan

Johnston

Ophoff

2019

Advances in Human-Computer Interaction

345

176

View full text Add to dashboard Cite

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“…Considering that other studies (Gopalan et al, 2017) have found that intrinsic motivation and academic achievement share significant and positive bonding and such motivation is able to spread the positivity and ensure long-term sustainability of the gained knowledge, we focused our research on this type of motivation.…”

Section: Course Design For Sufficient User Behavior Data Generationmentioning

confidence: 99%

“…Although external evaluation may motivate action, it may not produce the desired result in the long run. Students can strive for rewards rather than their knowledge, that's why it is very important that students are motivated by intrinsic motivation (Gopalan et al, 2017).…”

Section: Course Design For Sufficient User Behavior Data Generationmentioning

confidence: 99%

TELECI Approach for e-Learning User Behavior Data Visualization and Learning Support Algorithm

Kapenieks¹,

Daugule²,

Kapenieks³

et al. 2020

BJMC

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The user behavior data generated in the TELECI learning environment with additional short, easy-to-use multiple-choice questions before and after each content subunit are used for visualization and correlation analysis. Three user behavior data clusters were identified in data landscape. The student behavior change among the TELECI-clusters was used for TELECI learning support algorithm design. The student performance data before and after learning the econtent were used for knowledge acquisition model design. This model is based on the assumption that knowledge acquisition of real e-content can be quantified by superposition of the impact of learning "perfect" content, too easy content, and too complicated content. The learner knowledge acquisition surface is calculated on this assumption. The data of real course learner knowledge acquisition are located on this surface as "telecides". Telecides are the visualization of the appropriateness of an e-content unit for the needs of the specific learner or learners target group.1

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