About this paper

Appears in:
Pages: 1960-1967
Publication year: 2010
ISBN: 978-84-614-2439-9
ISSN: 2340-1095

Conference name: 3rd International Conference of Education, Research and Innovation
Dates: 15-17 November, 2010
Location: Madrid, Spain

PRELIMINARY DEVELOPMENT OF LEARNER SUPPORT PREDICTION MODEL FOR E-LEARNING BASED ON SELF-REGULATED LEARNING FACTORS

Y. Goda1, M. Yamada2, H. Kato3, T. Matsuda4, Y. Saito5, H. Miyagawa5

1Kumamoto University (JAPAN)
2Kanazawa University (JAPAN)
3The Open University of Japan (JAPAN)
4Yamagata University (JAPAN)
5Aoyama Gakuin University (JAPAN)
The purpose of this research is to develop learner support prediction model for e-learning courses based on self-regulated learning (SRL) factors. The model aims to predict learners’ needs and typical behavior to help them complete e-learning courses without any face-to-face instruction. There found four SRL factors including (1)cognitive, (2)affective, (3)help-seek, and (4)self-directed factors to determine learner types at the forethought phase of Zimmerman’s three-phase model for SRL (1998). The standardized questionnaire for SRL skills developed by Wolter, Pintrich, & Karabenic (2003) were modified and shorten based on the exploratory and confirmatory factor analysis results and it was utilized as an instrument. It consisted of 40 questions and had high reliability (Chronbach alpha = .931). The subjects included 305 students from three e-learning classes without any face-to-face instruction. In order to develop a preliminary model, 149 students’ data were analyzed and the model validation was done with other data of 156 students. The learner types were categorized as a result of a combination of three levels (positive, neutral, negative) for each SRL factor. Among 81 learner types (3*3*3*3), the types with the upper 27% and lower 27% on a completion rate of a course were selected. Then using the selected data, the multiple regression correlation and path analysis were performed for SRL factors on the completion rate. The significance of this research is to provide information on learners’ needs priori to a semester, which helps instructors and mentors to plan learner support and estimate necessary efforts to help students complete a course.
@InProceedings{GODA2010PRE,
author = {Goda, Y. and Yamada, M. and Kato, H. and Matsuda, T. and Saito, Y. and Miyagawa, H.},
title = {PRELIMINARY DEVELOPMENT OF LEARNER SUPPORT PREDICTION MODEL FOR E-LEARNING BASED ON SELF-REGULATED LEARNING FACTORS},
series = {3rd International Conference of Education, Research and Innovation},
booktitle = {ICERI2010 Proceedings},
isbn = {978-84-614-2439-9},
issn = {2340-1095},
publisher = {IATED},
location = {Madrid, Spain},
month = {15-17 November, 2010},
year = {2010},
pages = {1960-1967}}
TY - CONF
AU - Y. Goda AU - M. Yamada AU - H. Kato AU - T. Matsuda AU - Y. Saito AU - H. Miyagawa
TI - PRELIMINARY DEVELOPMENT OF LEARNER SUPPORT PREDICTION MODEL FOR E-LEARNING BASED ON SELF-REGULATED LEARNING FACTORS
SN - 978-84-614-2439-9/2340-1095
PY - 2010
Y1 - 15-17 November, 2010
CI - Madrid, Spain
JO - 3rd International Conference of Education, Research and Innovation
JA - ICERI2010 Proceedings
SP - 1960
EP - 1967
ER -
Y. Goda, M. Yamada, H. Kato, T. Matsuda, Y. Saito, H. Miyagawa (2010) PRELIMINARY DEVELOPMENT OF LEARNER SUPPORT PREDICTION MODEL FOR E-LEARNING BASED ON SELF-REGULATED LEARNING FACTORS, ICERI2010 Proceedings, pp. 1960-1967.
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