An Investigation on Task Difficulty: Does Task Difficulty Depend on the Technology Used in Task Completion?

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2024

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Association for Computing Machinery, Inc

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Information Systems Engineering
Information Systems is an academic and professional discipline which follows data collection, utilization, storage, distribution, processing and management processes and modern technologies used in this field. Our department implements a pioneering and innovative education program that aims to raise the manpower, able to meet the changing and developing needs and expectations of our country and the world. Our courses on current information technologies especially stand out.

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Abstract

Previous research indicates that task difficulty (i.e., students' judgments on a task's complexity) impacts their task performance. However, whether students' perceived task difficulty changes depending on the technology they use when completing tasks is still under investigation. The present study aims to address this gap in the literature. One hundred twenty-three students completed the study procedures. Students were randomly assigned to one of four groups (one control group and three experimental groups). Students were not allowed to use any technology in the control group. In contrast, those in experimental groups were permitted to use one of the following tools: e-textbook, Google, and ChatGPT. Students in each group completed three tasks with different complexities in the same order. The data was analyzed using repeated-measures ANOVA. The study revealed a significant interaction effect between groups and task difficulty perceptions at three levels. In all groups, perceived difficulty increased as the task complexity increased, but the change in students' perceived task difficulty across three tasks was impacted by the tool used when completing the tasks. © 2024 Owner/Author.

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ACM SIGCSE; Association for Computing Machinery (ACM)

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generative AI, task difficulty, task performance

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SIGCSE 2024 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education -- 55th ACM Technical Symposium on Computer Science Education, SIGCSE 2024 -- 20 March 2024 through 23 March 2024 -- Portland -- 197936

Volume

2

Issue

Start Page

1552

End Page

1553

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