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Experimental analysis of students' course selection
Author(s) -
Babad Elisha,
Tayeb Arik
Publication year - 2003
Publication title -
british journal of educational psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.557
H-Index - 95
eISSN - 2044-8279
pISSN - 0007-0998
DOI - 10.1348/000709903322275894
Subject(s) - psychology , dilemma , mathematics education , selection (genetic algorithm) , weighting , value (mathematics) , dimension (graph theory) , style (visual arts) , statistics , computer science , mathematics , artificial intelligence , medicine , history , geometry , archaeology , pure mathematics , radiology
Background: Prior to every term, students must select courses (i.e., academic units of instruction within a degree programme) to determine their study programme. Course selection (CS) is a sequential decision‐making (DM) process — students weigh various types of information available about each course. Every decision influences the weighting of considerations for the next. This study is focused on three central dimensions of CS: Learning Value (low or high in being intellectually challenging, interesting and thought‐provoking), Lecturer's Style (low or high — exciting, charismatic and humorous versus dry, inflexible, unclear, etc.), and Course Difficulty (easy, moderate or hard). Aims: (1) To examine students' preferences for each dimension in five choices and in their sequential location (1st to 5th). (2) To trace compromises in dilemma situations after the desirable combinations had already been selected. (3) To investigate differential selection as a function of students' age, gender, and academic standing (average grades). Sample: Advanced undergraduates in various departments in an Israeli university ( N =1,007). Method: In an experimental design, respondents were presented with 12 course descriptions representing 2×2×3 combinations, and asked to select five courses in a sequential order. Results: The 12 courses were found to be empirically divided into: ideal courses (2), first‐degree (4) and second‐degree (4) compromises, and rejected courses (2). Students avoided selecting hard courses unless they had no choice. Learning Value was the most preferred dimension, followed closely by Lecturer Style. Correlations showed that older and higher achieving students chose more difficult and high Learning Value courses. Comments: The discussion centred on the methodological issue of the effectiveness of an experimental design for the investigation of CS, conceptual issues concerning Course Difficulty in students' selection and evaluation, and applied issues concerning the availability of information about the three investigated dimensions to students in real‐life CS.