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Strömbäck, Filip; Mannila, Linda; Kamkar, Mariam – Informatics in Education, 2021
Concurrency is often perceived as difficult by students. One reason for this may be due to the fact that abstractions used in concurrent programs leave more situations undefined compared to sequential programs (e.g., in what order statements are executed), which makes it harder to create a proper mental model of the execution environment. Students…
Descriptors: College Students, Programming, Programming Languages, Concept Formation
Thoma, Athina; Iannone, Paola – International Journal of Research in Undergraduate Mathematics Education, 2022
This exploratory study reports on characteristics of proof production and proof writing observed in the work of first-year university students who took part in workshops on the theorem prover LEAN (https://leanprover.github.io). These workshops were voluntary and offered alongside a transition to proof module in a UK university. Through…
Descriptors: Validity, Mathematical Logic, Mathematics Instruction, Undergraduate Students
Aljumaily, Harith; Cuadra, Dolores; Laefer, Debra F. – Computer Science Education, 2019
Background: Conceptual models are an essential phase in software design, but they can create confusion and reduced performance for students in Database Design courses. Objective: A novel Relational Data Model Validation Tool (MVTool) was developed and tested to determine (1) if students who use MVTool perform better than those who do not, and (2)…
Descriptors: Models, Databases, Computer Science Education, Skills
Srour, F. Jordan; Karkoulian, Silva – International Journal of Social Research Methodology, 2022
The literature provides multiple measures of diversity along a single demographic dimension, but when it comes to studying the interaction of multiple diversity types (e.g. age, gender, and race), the field of useable measures diminishes. We present the use of decision trees as a machine learning technique to automatically identify the…
Descriptors: Diversity, Decision Making, Artificial Intelligence, Correlation