印美大学数字文化课程中基于视频游戏的评估数据集。

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Miguel Cobos
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引用次数: 0

摘要

该数据集包含了从 2022 年 10 月到 2024 年 8 月期间,印度洋大学对六个不同学科专业的大学一年级学生进行的基于视频游戏的评估结果。这些数据是通过 ClassTools.net 平台使用改编版《吃豆人》收集的,其中将传统的测验问题融入了游戏机制。数据集包括法律、医学、心理学、临床心理学、建筑学和护理学专业学生的 1418 次评估尝试,记录了他们在数字文化和计算机课程中的表现。每条记录包括尝试编号、时间戳、学生标识符、性别、学制、章节、职业项目和成绩。通过该数据集,可以分析学生的成绩模式、多次尝试的学习进度,以及不同学制和不同时期的比较研究。这些信息可为高等教育中的教育游戏化、评估设计和数字化学习策略研究提供支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dataset of video game-based assessments in digital culture courses at Indoamerica University
This dataset contains evaluation results from video game-based assessments administered to first-level university students across six different academic programs at Universidad Indoamérica from October 2022 to August 2024. The data were collected using an adapted version of Pacman through the ClassTools.net platform, where traditional quiz questions were integrated into gameplay mechanics. The dataset comprises 1418 assessment attempts from students in Law, Medicine, Psychology, Clinical Psychology, Architecture, and Nursing programs, documenting their performance in digital culture and computing courses. Each record includes attempt number, timestamp, student identifier, gender, academic period, section, career program, and score achieved. The dataset enables analysis of student performance patterns, learning progression through multiple attempts, and comparative studies across different academic programs and periods. This information can support research in educational gamification, assessment design, and digital learning strategies in higher education.
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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