Mind the Gap: Confronting the Vast Divide Between CS Teaching and Machine Learning Pedagogy

Shai Perach, Giora Alexandron

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The increasing demand for machine learning and deep learning (ML/DL) education spans K-12, college, and vocational training, highlighting the urgent need to prepare Computer Science (CS) teachers for these fields. This study aims to characterize the knowledge gaps and challenges experienced by CS teachers as they transition to teaching a rigorous ML curriculum. The paper attempts to achieve this in two distinct and self-contained ways: first, through a theoretical analysis conducted via a literature review examined through the lens of theoretical frameworks, and second, through an empirical qualitative analysis of a case study involving CS teachers transitioning to ML education. The empirical analysis echoes the findings of the theoretical analysis and sharpens them with additional insights. Our findings reveal significant difficulties, such as relearning mathematical foundations, adapting to new problem-solving paradigms, and developing ML-specific pedagogical content knowledge. Notably, the existing expertise of experienced CS teachers has limited relevance to ML/DL education, raising the question of why we focus mainly on CS teachers as the potential teaching workforce to train. The discussion integrates the theoretical and empirical findings to offer conclusions and recommendations for educational institutions, policymakers, and teacher training programs in enhancing ML/DL teaching capacities across various academic levels.

Original languageEnglish
Title of host publicationTechnology Enhanced Learning for Inclusive and Equitable Quality Education
Subtitle of host publication19th European Conference on Technology Enhanced Learning, EC-TEL 2024, Krems, Austria, September 16–20, 2024, Proceedings, Part I
EditorsRafael Ferreira Mello, Nikol Rummel, Ioana Jivet, Gerti Pishtari, José A. Ruipérez Valiente
PublisherSpringer Science and Business Media B.V.
Pages344-358
Number of pages15
ISBN (Print)9783031723148
DOIs
StatePublished Online - 13 Sep 2024
Event19th European Conference on Technology Enhanced Learning, EC-TEL 2024 - Krems, Austria
Duration: 16 Sep 202420 Sep 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume15159 LNCS

Conference

Conference19th European Conference on Technology Enhanced Learning, EC-TEL 2024
Country/TerritoryAustria
CityKrems
Period16/09/2420/09/24

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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