[This paper is part of the Focused Collection on Qualitative Methods in PER: A Critical Examination.] Qualitative research methods have provided key insights in physics education research (PER) by drawing on non-numerical data such as text or video data. While different methods towards qualitative research exist, they share two essential steps:…

Artificial intelligence (AI) technologies have been consistently influencing the progress of education for an extended period, with its impact becoming more significant especially after the launch of ChatGPT-3.5 at the end of November 2022. In the field of physics education, recent research regarding the performance of ChatGPT-3.5 in solving…

Physics education researchers are interested in using the tools of machine learning and natural language processing to make quantitative claims from natural language and text data, such as open-ended responses to survey questions. The aspiration is that this form of machine coding may be more efficient and consistent than human coding, allowing…

Recent advances in publicly available natural language processors (NLP) may enhance the efficiency of analyzing student short-answer responses in physics education research (PER). We train a state-of-the-art NLP, IBM's Watson, and test its agreement with human coders using two different studies that gathered text responses in which students…

Surveys have long been used in physics education research to understand student reasoning and inform course improvements. However, to make analysis of large sets of responses practical, most surveys use a closed-response format with a small set of potential responses. Open-ended formats, such as written free response, can provide deeper insights…

This work explores the integration of artificial intelligence (AI) custom chatbots in educational settings, with a particular focus on their applicability in the context of mathematics and physics. In view of the increasing deployment of AI tools such as ChatGPT in educational contexts, the present study explores their potential in generating…

Generative AI technologies such as large language models show novel potential to enhance educational research. For example, generative large language models were shown to be capable of solving quantitative reasoning tasks in physics and concept tests such as the Force Concept Inventory (FCI). Given the importance of such concept inventories for…

Massive pretrained language models have garnered attention and controversy due to their ability to generate humanlike responses: Attention due to their frequent indistinguishability from human-generated phraseology and narratives and controversy due to the fact that their convincingly presented arguments and facts are frequently simply false. Just…

We investigated the feasibility of using automatic speech recognition (ASR) and natural language processing (NLP) to classify collaborative problem solving (CPS) skills from recorded speech in noisy environments. We analyzed data from 44 dyads of middle and high school students who used videoconferencing to collaboratively solve physics and math…

The recent advancement of large language models presents numerous opportunities for teaching and learning. Despite widespread public debate regarding the use of large language models, empirical research on their opportunities and risks in education remains limited. In this work, we demonstrate the qualities and shortcomings of using ChatGPT 3.5…

In the age of rapid technological advancements, the integration of Artificial Intelligence (AI), machine learning (ML), and large language models (LLMs) in Science, Technology, Engineering, and Mathematics (STEM) education has emerged as a transformative force, reshaping pedagogical approaches and assessment methodologies. "Uses of AI in STEM…

Pedagogic Conversational Agents are computer applications that can interact with students in natural language. They have been used with satisfactory results on the instruction of several domains. The authors believe that they could also be useful for the instruction of Secondary Physics and Chemistry Education. Therefore, in this paper, the…

The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…