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Social and Behavioral Sciences Commons™
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Full-Text Articles in Social and Behavioral Sciences
Smartphones And Learning: An Extension Of M-Learning Or A Distinct Area Of Inquiry, Kendall Hartley, Alberto Andújar
Smartphones And Learning: An Extension Of M-Learning Or A Distinct Area Of Inquiry, Kendall Hartley, Alberto Andújar
Teaching and Learning Faculty Research
The smartphone has become an integral part of the education landscape. While there has been significant smartphone research in education under the guise of m-learning, the unique role of the device suggests that m-learning may not be an appropriate characterization. The purpose of this paper is to review the use of m-learning as a primary descriptor for smartphone-and learning-related research. In support of this goal, the paper reviews the definitions associated with m-learning, smartphones, and related technologies from the perspective of educational research. In addition, a review of author keywords of research on smartphones in education is used to provide …
Conducting A Formative Evaluation On A Course-Level Learning Analytics Implementation Through The Lens Of Self-Regulated Learning And Higher-Order Thinking, Pauline S. Muljana, Tian Luo, Greg Placencia
Conducting A Formative Evaluation On A Course-Level Learning Analytics Implementation Through The Lens Of Self-Regulated Learning And Higher-Order Thinking, Pauline S. Muljana, Tian Luo, Greg Placencia
STEMPS Faculty Publications
Self-regulated learning (SRL) and higher-order thinking skills (HOTS) are associated with academic achievement, but fostering these skills is not easy. Scholars have suggested an alternative way to scaffold these important skills through learning analytics (LA). This paper presents a formative evaluation of a course-level LA implementation through the lens of self-regulated learning (SRL) and higher-order thinking skills (HOTS). We explored the changes in students’ SRL, HOTS, and perceptions at the end of the course term. Results indicate an increase in some elements of SRL and HOTS, and positive student perceptions. Discussion on implications and opportunities for informing future teaching strategies …
Assessment And Learning In Knowledge Spaces (Aleks) Adaptive System Impact On Students' Perception And Self-Regulated Learning Skills, Honda Harati, Laura Sujo-Montes, Chih-Hsiung Tu, Shadow J.W. Armfield, Cherng-Jyh Yen
Assessment And Learning In Knowledge Spaces (Aleks) Adaptive System Impact On Students' Perception And Self-Regulated Learning Skills, Honda Harati, Laura Sujo-Montes, Chih-Hsiung Tu, Shadow J.W. Armfield, Cherng-Jyh Yen
Educational Foundations & Leadership Faculty Publications
Adaptive learning is an educational method that uses computer algorithms and artificial intelligence (AI) to customize learning materials and activities based on each user's model. Adaptive learning has been used for more than 20 years. However, it is still unique, and no other system could bring more or even similar capabilities than the ones adaptive technology offers, including the application of AI, psychology, psychometrics, machine learning, and providing a personalized learning environment. However, there are not many studies on its practicality, usefulness, improving students' learning skills, students' perception, etc., due to the limited number of institutes investing in this new …
Development Of The Smartphone And Learning Inventory: Measuring Self-Regulated Use, Kendall Hartley, Lisa D. Bendixen, Lori Olafson, Dan Gianoutsos, Emily Shreve
Development Of The Smartphone And Learning Inventory: Measuring Self-Regulated Use, Kendall Hartley, Lisa D. Bendixen, Lori Olafson, Dan Gianoutsos, Emily Shreve
Teaching and Learning Faculty Research
Smartphone use in learning environments can be productive or distracting depending upon the type of use. The use is also impacted by the learner’s view and understanding of the smartphone and self-regulated learning skills. Measures are needed to specify uses and learner understandings to address the implications for teaching and learning. This study reports on the development of a multi-factor inventory designed to measure multitasking while studying, avoiding distractions while studying, mindful phone use, and phone knowledge. The inventory was completed by 514 undergraduate students enrolled in a first-year seminar. The results indicate good reliability and a three-factor structure with …