Software Engineering Skillset Assessment Dataset for Computer Science Students
Description
The Software Engineering Skillset Dataset comprises Soft Skills, Life Skills, and Technical Skills, which are key components for evaluating and predicting the software engineering competencies of computer science students. The surveys, conducted using a meticulously crafted questionnaire, served as the primary data collection method, targeting computer science students in software engineering courses across higher educational institutions in Kerala, India. This extensive survey engaged over two thousand students, evaluating each skill category through a dedicated assessment quiz comprising a total of fifteen questions. The survey was designed to assess Soft Skills, Life Skills, and Technical Skills through a series of questions, each employed a six-point scale for responses as follows: 0: "Never" 1: "Rarely" 2: "Sometimes" 3: "Often" 4: "Mostly" 5: "Always" The dataset, designed as a classification problem, features two distinct classes (0 and 1). Participants scoring above 60% in each skill area are classified as proficient. The survey comprises three segments and 54 questions for a detailed evaluation of the skills: 1. Soft Skills: Assessed through five tests covering 18 attributes. 2. Life Skills: Evaluated through five tests focusing on nine attributes, emphasizing workplace practices and developmental strategies. 3. Technical Skills: Measured via five tests with nine specific features. This dataset not only enables a comprehensive analysis of individual and combined skills but also provides valuable insights for students, highlighting their academic strengths and areas needing improvement.
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Steps to reproduce
The questionnaire and prompts used in this study are detailed and discussed in the following two manuscripts: 1. Nizar, J., Sharmila, R., and Jaseena, K.U. (2024). A Random Forest Model for Prediction of Software Engineering Skill Set among Computer Science Students through Explainable AI. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 2633–2650. 2. Nizar, J., Sharmila, R., and Jaseena, K.U. (2024). Prediction and Assessment of Software Engineering Skillset Among Computer Science Students Using Convolutional Neural Networks through Explainable AI. Journal of Theoretical and Applied Information Technology, 102(21).