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Comparing lesson plan-driven and ask-me-anything chatbots: teaching a UNIX Shell course.

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Title: Comparing lesson plan-driven and ask-me-anything chatbots: teaching a UNIX Shell course.
Authors: Berengueres, Jose1,2 (AUTHOR) josebere@kth.se
Source: Discover Education. 4/30/2025, Vol. 4 Issue 1, p1-23. 23p.
Subject Terms: *Lesson planning, *Education methodology, *Course evaluation (Education), *Inquiry-based learning, Chatbots
Abstract: GPT-based models have enabled the creation of natural language chatbots that support both Inquiry-Based and Structured Learning approaches. This study offers a direct comparison of these two paradigms within a UNIX Shell scripting course by means of two chatbots: a Lesson Plan-Driven chatbot that ensures all students cover the same topics systematically, and an Ask-Me-Anything (AMA) chatbot more suited to exploratory learning. We compared two particular chatbots—Harvard's CS50 (as an AMA chatbot) and OS315 (ours), as a lesson plan-driven chatbot—through four surveys. Results show a Net Promoter Score (NPS) of + 45 CI[25, 66] (N = 55) for the least performing lesson plan-driven chatbot and + 35 CI[11, 58.5] (N = 40) for the AMA chatbot. The majority of students favored a blend of human and chatbot instruction. Additionally, we discuss factors such as cost, accessibility, and why the same chatbot architecture, when applied to a Data Visualization course yields a lower NPS of + 9 CI[−6, + 23]. [ABSTRACT FROM AUTHOR]
Copyright of Discover Education is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: GPT-based models have enabled the creation of natural language chatbots that support both Inquiry-Based and Structured Learning approaches. This study offers a direct comparison of these two paradigms within a UNIX Shell scripting course by means of two chatbots: a Lesson Plan-Driven chatbot that ensures all students cover the same topics systematically, and an Ask-Me-Anything (AMA) chatbot more suited to exploratory learning. We compared two particular chatbots—Harvard's CS50 (as an AMA chatbot) and OS315 (ours), as a lesson plan-driven chatbot—through four surveys. Results show a Net Promoter Score (NPS) of + 45 CI[25, 66] (N = 55) for the least performing lesson plan-driven chatbot and + 35 CI[11, 58.5] (N = 40) for the AMA chatbot. The majority of students favored a blend of human and chatbot instruction. Additionally, we discuss factors such as cost, accessibility, and why the same chatbot architecture, when applied to a Data Visualization course yields a lower NPS of + 9 CI[−6, + 23]. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Discover Education is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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