Study strategies in a computer assisted study environment

被引:35
作者
Beishuizen, JJ [1 ]
Stoutjesdijk, ET [1 ]
机构
[1] Leiden Univ, Dept Dev & Educ Psychol, NL-2300 RB Leiden, Netherlands
关键词
D O I
10.1016/S0959-4752(98)00027-9
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
A Computer Assisted Study Environment (CASE) was developed as a tool for diagnosing study problems, to be used together with other sources of information, such as learning style questionnaires and clinical interviews. Forty-one students were observed during a 1 h period of studying a text book chapter in CASE. The stages of orientation, planning, and execution were clearly separated by dividing the 1 h study session into three periods. Students could spend an unlimited part of the hour on orientation (first period). Then, not included within the hour, a plan for the task had to be made (second period), after which the remaining time could be devoted to execution of the plan or to any other form of study (third period). We administered a learning style questionnaire, measured reading speed and pretested the students on prior knowledge of the content of the study task. These data were correlated with product and process indicators collected in CASE in order to find out whether various sources of information about learning styles and study strategies provided converging evidence about potential causes of study problems. Process and product indicators of study strategies in CASE revealed differences between deep and surface learning students in orientation and planning activities. However, their actual study behaviour did not vary according to learning style. So, the differences between surface and deep learning become more apparent when we look at study activities before and after actual reading and processing information. As far as learning outcomes are concerned, students with a deep learning style obtained better results than students with a surface learning style, even for factual knowledge. Deep learning students knew more about the subject of the diagnostic study task, and developed a higher reading speed. Both student characteristics significantly determined learning outcomes. (C) 1999 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:281 / 301
页数:21
相关论文
共 28 条
[11]  
Entwistle N.J., 1983, Understanding student learning
[12]  
GLEITMAN H, 1986, PSYCHOL
[13]   DOING THE SAME WORK WITH HARD COPY AND WITH CATHODE-RAY TUBE (CRT) COMPUTER TERMINALS [J].
GOULD, JD ;
GRISCHKOWSKY, N .
HUMAN FACTORS, 1984, 26 (03) :323-337
[14]  
KALDEWAY J, 1990, TERUGBLIK 10 JAAR ST, P153
[15]   Discontinuities and continuities in the experience of learning: An interview study of high-school students in Hong Kong [J].
Marton, F ;
Watkins, D ;
Tang, C .
LEARNING AND INSTRUCTION, 1997, 7 (01) :21-48
[16]  
Marton F., 1997, The experience of learning, P39
[17]   THE EFFECTS OF TEST EXPECTANCY ON PROCESSING AND MEMORY OF PROSE [J].
MCDANIEL, MA ;
BLISCHAK, DM ;
CHALLIS, B .
CONTEMPORARY EDUCATIONAL PSYCHOLOGY, 1994, 19 (02) :230-248
[18]   STYLES AND STRATEGIES OF LEARNING [J].
PASK, G .
BRITISH JOURNAL OF EDUCATIONAL PSYCHOLOGY, 1976, 46 (JUN) :128-148
[19]   RELIABILITY AND PREDICTIVE-VALIDITY OF THE MOTIVATED STRATEGIES FOR LEARNING QUESTIONNAIRE (MSLQ) [J].
PINTRICH, PR ;
SMITH, DAF ;
GARCIA, T ;
MCKEACHIE, WJ .
EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT, 1993, 53 (03) :801-813
[20]   DOMAIN EXPERTISE AND KNOWLEDGE ACQUISITION FROM NONLINEAR EXPOSITORY TEXT [J].
SAMARAPUNGAVAN, A ;
BEISHUIZEN, J .
COMPUTERS IN HUMAN BEHAVIOR, 1994, 10 (01) :77-91