Hilde Thygesen, Astrid Gramstad, Lene A. Åsli, Linda Stigen, Trine A. Magne, Tove Carstensen and Tore Bonsaksen
Student satisfaction is an important indicator of educational quality in higher education institutions. Learning environment factors are assumed to play a role in determining…
Abstract
Purpose
Student satisfaction is an important indicator of educational quality in higher education institutions. Learning environment factors are assumed to play a role in determining student satisfaction. The purpose of this study is to examine the intrinsic relationships between five learning environment scales embedded within one measure; and examine the associations between each of these scales and an overall measure of education program satisfaction.
Design/methodology/approach
In this cross-sectional study, 175 first-year occupational therapy students in Norway completed sociodemographic information and the Course Experience Questionnaire. The data were analyzed with Pearson’s correlation coefficient r and with linear regression.
Findings
All intrinsic associations between the learning environment scales were positive. In the adjusted analysis, higher education program satisfaction was significantly associated with higher scores on “clear goals and standards,” “emphasis on independence” and “good teaching.” The final model accounted for 45.0% of the outcome variance, of which the scores on the learning environment scales contributed 41.8%.
Originality/value
The learning environment is vital for student satisfaction. More specifically, efforts to improve student satisfaction may include strengthening student-focused teaching, strengthening the autonomy of the students, and ensuring that the goals and standards of courses are clear and easy to understand.
Details
Keywords
Even Elias Edvardsen, Eline Fjærestad Dalseth, Susanne Grødem Johnson, Linda Stigen, Gry Mørk, Trine A. Magne, Astrid Gramstad, Milada Cvancarova Småstuen and Tore Bonsaksen
Understanding students’ preferences for teaching and course design is important for educators in higher education when planning courses and teaching activities. The purpose of…
Abstract
Purpose
Understanding students’ preferences for teaching and course design is important for educators in higher education when planning courses and teaching activities. The purpose of this study was to explore changes in occupational therapy students’ preferences for teaching and courses across the three-year study program.
Design/methodology/approach
A total of 263 students participated in a longitudinal study, where preferences were measured with the Approaches and Study Skills Inventory for Students. The data were analyzed with linear mixed effect models for repeated measures.
Findings
The results indicated no significant changes in preferences for courses and teaching over the three-year period. Also, there were no significant differences between the six involved study programs. Preferences for the courses and teaching type “supporting understanding” were associated with higher age and higher study effort. Preferences for the courses and teaching type “transmitting information” were associated with lower age and female gender.
Originality/value
In summary, the findings of this study suggest that preferences for teaching and courses are stable and may be challenging to alter during a three-year undergraduate study program.
Details
Keywords
Arash Joorabchi and Abdulhussain E. Mahdi
This paper aims to report on the design and development of a new approach for automatic classification and subject indexing of research documents in scientific digital libraries…
Abstract
Purpose
This paper aims to report on the design and development of a new approach for automatic classification and subject indexing of research documents in scientific digital libraries and repositories (DLR) according to library controlled vocabularies such as DDC and FAST.
Design/methodology/approach
The proposed concept matching-based approach (CMA) detects key Wikipedia concepts occurring in a document and searches the OPACs of conventional libraries via querying the WorldCat database to retrieve a set of MARC records which share one or more of the detected key concepts. Then the semantic similarity of each retrieved MARC record to the document is measured and, using an inference algorithm, the DDC classes and FAST subjects of those MARC records which have the highest similarity to the document are assigned to it.
Findings
The performance of the proposed method in terms of the accuracy of the DDC classes and FAST subjects automatically assigned to a set of research documents is evaluated using standard information retrieval measures of precision, recall, and F1. The authors demonstrate the superiority of the proposed approach in terms of accuracy performance in comparison to a similar system currently deployed in a large scale scientific search engine.
Originality/value
The proposed approach enables the development of a new type of subject classification system for DLR, and addresses some of the problems similar systems suffer from, such as the problem of imbalanced training data encountered by machine learning-based systems, and the problem of word-sense ambiguity encountered by string matching-based systems.