IEEE International Conference on Advanced Learning Technologies

Learning Technologies
Learning Technologies

The 18th IEEE International Conference on Advanced Learning Technologies

Track Description and Topics of Interest:
Motivational and affective aspects of learning with technologies continue to be important areas of research for teaching and learning. Research in this area may involve teachers’ and/or learners’ perceptions, attitudes, perspectives, beliefs, preferences, self-efficacy, motivation, engagement, attention, concentration, anxiety or emotions in technology-enhanced teaching and learning.

In particular, the volume of research on the role of emotion in learning and performance has increased in recent years. However, the reciprocal functions of motivational and affective aspects in learning still need further examination, especially in technology-enhanced learning environments. For example, understanding both learner motivation and learner emotion can inform how to design or revise an online course. In addition, detecting or tracking student learning states, especially the motivational and affective states, in technology-enhanced learning environments can contribute to the design of adaptive learning experiences. Thus, ICALT2018 invites proposals focusing on integrative views of motivational and affective aspects of learning with technologies.

Topics of interest include, but are not limited to:

1. Views of motivational and affective theories in technology-enhanced learning
2. Impacts of motivational and affective factors on learning with technology
3. Interactions between cognition and affect in technology-enhance learning
4. Individual differences in affective measurements in technology-enhanced learning
5. Instruments for assessing affective variables in technology-enhanced learning
6. Methods for detecting or tracking motivational and affective states in learning process
7. Affective computing in technology-enhanced learning environments
8. Modeling, enactment and intelligent use of affective computing
9. Motivational and affective regulation in technology-enhanced learning environment
10. Design of scaffoldings based on motivational and affective evaluation
11. Design of affective learning companions or emotive agents
12. Teachers’ motivational and affective issues on the use of technology-enhanced learning
13. Designing and revising technology-enhanced learning environments based on learner affect
14. Detecting or tracking student visual behaviors in technology-enhanced learning
15. Human computer interaction in technology-enhanced learning environment
16. Other topics related to motivational and affective issues in learning with technology

Track Program Committee
Lucia Barron, Instituto Tecnológico de Culiacán, Mexico
Min-Yuh Day, Tamkang University, Taiwan
Pradipta De, Georgia Southern University, USA
Vanessa Dennen, Florida State University, USA
HuiChen Durley, Oklahoma City Public Schools, USA
Demetria Ennis-Cole, University of North Texas, USA
Chris Faulkner, University of North Texas, USA
Ulla Freihofner, The University of Queensland, Australia
Xun Ge, University of Oklahoma, USA
Giner Alor Hernandez, Instituto Tecnologico de Orizaba, Mexico
Min-Chai Hsieh, National University of Tainan, Taiwan
Hale Ilgaz, Ankara University, Turkey
Christie Liu, James Madison University, USA
Carlos Alberto Reyes Garcia, Instituto Nacional de Astrofisica Optica Y Electronica, Mexico
Harry Santoso, University of Indonesia, Indonesia
Valerie Shute, Florida State University, USA
Hakan Tüzün, Hacettepe University, Turkey
Jiangmei Yuan, West Virginia University, USA

http://www.et.iitb.ac.in/icalt2018/index.html

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