A new course difficulty index (CDf): Framework and application

A new framework for the quantification of course difficulty in academic curricula is proposed. The originality of the approach lies in its course-centric nature. A course difficulty index value is calculated (CDf ), using difficulty indicators that characterize the course as a whole. The difficulty indicators can be tailored to reflect the academic domain considered. A weighting percentage is calculated and it is assigned to each course difficulty indicator, by systematically conducting Principal Component Analysis (PCA) on students? assessment data. Next, the weighted difficulty indicators are used to calculate CDf in the form of a composite indicator. In general, the value of the latter varies across courses, and across different offerings of a given course. The CDf framework is applied in the case of a university in Greece by utilizing course difficulty indicators which are objective in their nature, like course mean and median grades, passing grade percentages, etc. The dataset used spans a period of thirteen (13) academic years. The findings are used to identify courses that represent ?bottlenecks? in student study paths. Subjective course difficulty indicators may also be used, like students? questionnaire data. It is worth noting that the quantification of course difficulty by means of a single index can be used in the calculation of adjusted student scores and, as such, facilitate data mining operations on students? assessment data. All in all, the proposed CDf framework and analysis comprise a useful tool for academic policy-making and quality assurance.

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Publication Details

Journal
Computer Science and Information Systems
Published
2024-11-05
DOI
https://doi.org/10.2298/csis240420068k
Primary Topic
Online Learning and Analytics
Type
article
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article

A new course difficulty index (CDf): Framework and application

Leonidas Karamitopoulos, Dimitris A. Dervos, Konstantinos Kelesidis
Computer Science and Information Systems
Online Learning and Analytics
article

A new course difficulty index (CDf): Framework and application

Leonidas Karamitopoulos, Dimitris A. Dervos, Konstantinos Kelesidis
article en

Abstract

A new framework for the quantification of course difficulty in academic curricula is proposed. The originality of the approach lies in its course-centric nature. A course difficulty index value is calculated (CDf ), using difficulty indicators that characterize the course as a whole. The difficulty indicators can be tailored to reflect the academic domain considered. A weighting percentage is calculated and it is assigned to each course difficulty indicator, by systematically conducting Principal Component Analysis (PCA) on students? assessment data. Next, the weighted difficulty indicators are used to calculate CDf in the form of a composite indicator. In general, the value of the latter varies across courses, and across different offerings of a given course. The CDf framework is applied in the case of a university in Greece by utilizing course difficulty indicators which are objective in their nature, like course mean and median grades, passing grade percentages, etc. The dataset used spans a period of thirteen (13) academic years. The findings are used to identify courses that represent ?bottlenecks? in student study paths. Subjective course difficulty indicators may also be used, like students? questionnaire data. It is worth noting that the quantification of course difficulty by means of a single index can be used in the calculation of adjusted student scores and, as such, facilitate data mining operations on students? assessment data. All in all, the proposed CDf framework and analysis comprise a useful tool for academic policy-making and quality assurance.

Computer Science and Information SystemsVol. 22(1)
International Hellenic University (GR)
Openalex Percentile: Top 79%
Online Learning and Analytics
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A new course difficulty index (CDf): Framework and application — Leonidas Karamitopoulos, Dimitris A. Dervos, et al. · Computer Science and Information Systems (2024) | TGRS Research Map | TGRS