CS Educator challenges and their solutions : A systematic mapping study
- URL: http://arxiv.org/abs/2511.02876v1
- Date: Tue, 04 Nov 2025 07:24:41 GMT
- Title: CS Educator challenges and their solutions : A systematic mapping study
- Authors: Anjali Chouhan, Sruti Srinivasa Ragavan, Amey Karkare,
- Abstract summary: It remains unclear which areas have been thoroughly addressed and which still lack sufficient scholarly attention.<n>Our analysis revealed recurring issues in areas such as assessment practices, teacher training, classroom management, and emotional well-being.
- Score: 0.9494669823390646
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Computer Science (CS) education is expanding rapidly, but educators continue to face persistent challenges in teaching and learning environments.Despite growing interest, limited systematic work exists to categorize and synthesize the specific challenges faced by CS educators and the remedies adopted in response.This is problematic because it remains unclear which areas have been thoroughly addressed and which still lack sufficient scholarly attention. In this study, we conducted a structured literature review of peer-reviewed research papers published over the last five years, focusing on challenges and remedies across ten categorized themes, including pedagogical, emotional, technological, and institutional dimensions.Our analysis revealed recurring issues in areas such as assessment practices, teacher training, classroom management, and emotional well-being, along with various strategies such as professional development programs and policy interventions adopted to mitigate them while also revealing several areas that have received insufficient attention.This review offers a consolidated understanding of the CS education landscape, providing valuable insights for researchers, curriculum designers, and policymakers aiming to improve teaching effectiveness and educator support.
Related papers
- A Survey of Deep Learning for Geometry Problem Solving [52.90604903858389]
Geometry problem solving is vital across various domains, including education, the assessment of AI's mathematical abilities, and multimodal capability evaluation.<n>The recent surge in deep learning technologies, particularly the emergence of multimodal large language models, has significantly accelerated research in this area.
arXiv Detail & Related papers (2025-07-16T06:03:08Z) - LLM Agents for Education: Advances and Applications [49.3663528354802]
Large Language Model (LLM) agents have demonstrated remarkable capabilities in automating tasks and driving innovation across diverse educational applications.<n>This survey aims to provide a comprehensive technological overview of LLM agents for education, fostering further research and collaboration to enhance their impact for the greater good of learners and educators alike.
arXiv Detail & Related papers (2025-03-14T11:53:44Z) - Assessing Pedagogical Readiness for Digital Innovation: A Mixed-Methods Study [0.0]
This study evaluates the preparation of instructors to use digital technologies into their educational practices.<n>The results show that even while a large number of educators acknowledge the benefits of digital tools, problems including poor professional development and change aversion still exist.
arXiv Detail & Related papers (2025-02-17T10:29:24Z) - Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges [60.62904929065257]
Large language models (LLMs) offer possibility for resolving this issue by comprehending individual requests.
This paper reviews the recently emerged LLM research related to educational capabilities, including mathematics, writing, programming, reasoning, and knowledge-based question answering.
arXiv Detail & Related papers (2023-12-27T14:37:32Z) - Ethical Challenges in Gamified Education Research and Development: An
Umbrella Review and Potential Directions [10.405048273969083]
Gamification is a technological, economic, cultural, and societal development toward promoting a more game-like reality.
This study explores ethical challenges in gamified educational applications and proposes potential solutions.
arXiv Detail & Related papers (2023-09-26T13:23:50Z) - Machine Unlearning: A Survey [56.79152190680552]
A special need has arisen where, due to privacy, usability, and/or the right to be forgotten, information about some specific samples needs to be removed from a model, called machine unlearning.
This emerging technology has drawn significant interest from both academics and industry due to its innovation and practicality.
No study has analyzed this complex topic or compared the feasibility of existing unlearning solutions in different kinds of scenarios.
The survey concludes by highlighting some of the outstanding issues with unlearning techniques, along with some feasible directions for new research opportunities.
arXiv Detail & Related papers (2023-06-06T10:18:36Z) - Remote Teaching and Learning in Applied Engineering: A Post-Pandemic
Perspective [0.548253258922555]
We provide a rationale for a variety of course delivery models at different stages of the pandemic.
We discuss how we ensured that hands-on learning remains an integral part of engineering curricula.
arXiv Detail & Related papers (2021-08-05T16:28:05Z) - Exploratory Learning Environments for Responsible Management Education
Using Lego Serious Play [0.0]
We will draw on constructivist learning theories and Lego Serious Play (LSP) as a learning enhancement approach to develop a pedagogical framework.
LSP is selected due to its increasing application in learning environments to help promote critical discourse, and engage with highly complex problems.
arXiv Detail & Related papers (2021-03-27T22:28:34Z) - The Challenges of Assessing and Evaluating the Students at Distance [77.34726150561087]
The COVID-19 pandemic has caused a strong effect on higher education institutions with the closure of classroom teaching activities.
This short essay aims to explore the challenges posed to Portuguese higher education institutions and to analyze the challenges posed to evaluation models.
arXiv Detail & Related papers (2021-01-30T13:13:45Z) - Neural Multi-Task Learning for Teacher Question Detection in Online
Classrooms [50.19997675066203]
We build an end-to-end neural framework that automatically detects questions from teachers' audio recordings.
By incorporating multi-task learning techniques, we are able to strengthen the understanding of semantic relations among different types of questions.
arXiv Detail & Related papers (2020-05-16T02:17:04Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.