TY - JOUR TI - Application of generative artificial intelligence (GenAI) in language teaching and learning: A scoping literature review AU - Law, Locky T2 - Computers and Education Open DA - 2024/06// PY - 2024 DO - 10.1016/j.caeo.2024.100174 DP - DOI.org (Crossref) VL - 6 SP - 100174 J2 - Computers and Education Open LA - en SN - 26665573 ST - Application of generative artificial intelligence (GenAI) in language teaching and learning UR - https://linkinghub.elsevier.com/retrieve/pii/S2666557324000156 Y2 - 2024/09/04/13:23:22 ER - TY - JOUR TI - The use of ChatGPT in teaching and learning: a systematic review through SWOT analysis approach AU - Mai, Duong Thi Thuy AU - Da, Can Van AU - Hanh, Nguyen Van T2 - Frontiers in Education AB - Introduction The integration of ChatGPT, an advanced AI-powered chatbot, into educational settings, has caused mixed reactions among educators. Therefore, we conducted a systematic review to explore the strengths and weaknesses of using ChatGPT and discuss the opportunities and threats of using ChatGPT in teaching and learning. Methods Following the PRISMA flowchart guidelines, 51 articles were selected among 819 studies collected from Scopus, ERIC and Google Scholar databases in the period from 2022-2023. Results The synthesis of data extracted from the 51 included articles revealed 32 topics including 13 strengths, 10 weaknesses, 5 opportunities and 4 threats of using ChatGPT in teaching and learning. We used Biggs’s Presage-Process-Product (3P) model of teaching and learning to categorize topics into three components of the 3P model. Discussion In the Presage stage, we analyzed how ChatGPT interacts with student characteristics and teaching contexts to ensure that the technology adapts effectively to diverse needs and backgrounds. In the Process stage, we analyzed how ChatGPT impacted teaching and learning activities to determine its ability to provide personalized, adaptive, and effective instructional support. Finally, in the Product stage, we evaluated how ChatGPT contributed to student learning outcomes. By carefully considering its application in each stage of teaching and learning, educators can make informed decisions, leveraging the strengths and addressing the weaknesses of ChatGPT to optimize its integration into teaching and learning processes. DA - 2024/02/09/ PY - 2024 DO - 10.3389/feduc.2024.1328769 DP - DOI.org (Crossref) VL - 9 SP - 1328769 J2 - Front. Educ. SN - 2504-284X ST - The use of ChatGPT in teaching and learning UR - https://www.frontiersin.org/articles/10.3389/feduc.2024.1328769/full Y2 - 2024/05/24/06:39:17 L1 - files/2844/Mai et al. - 2024 - The use of ChatGPT in teaching and learning a sys.pdf ER - TY - CHAP TI - Solving the Self-regulated Learning Problem: Exploring the Performance of ChatGPT in Mathematics AU - Li, Pin-Hui AU - Lee, Hsin-Yu AU - Cheng, Yu-Ping AU - Starčič, Andreja Istenič AU - Huang, Yueh-Min T2 - Innovative Technologies and Learning A2 - Huang, Yueh-Min A2 - Rocha, Tânia CY - Cham DA - 2023/// PY - 2023 DP - DOI.org (Crossref) VL - 14099 SP - 77 EP - 86 LA - en PB - Springer Nature Switzerland SN - 978-3-031-40112-1 978-3-031-40113-8 ST - Solving the Self-regulated Learning Problem UR - https://link.springer.com/10.1007/978-3-031-40113-8_8 Y2 - 2024/05/23/07:12:16 ER - TY - JOUR TI - Pre-service teachers and ChatGPT in multistrategy problem-solving: Implications for mathematics teaching in primary schools AU - Getenet, Seyum T2 - International Electronic Journal of Mathematics Education AB - This study compared the problem-solving abilities of ChatGPT and 58 pre-service teachers (PSTs) in solving a mathematical word problem using various strategies. PSTs were asked to solve a problem individually. Data was collected from PSTs’ submitted assignments, and their problem-solving strategies were analyzed. ChatGPT was also given the same problem to solve with various prompts, and the correctness of its solutions and problem-solving strategies were assessed alongside those of PSTs. The results indicated that PSTs used diverse strategies and achieved accurate solutions, but not always relevant strategies to children’s level of understanding. ChatGPT employed similar strategies to PSTs but mostly produced incorrect solutions, and its performance needed to be contextualized in the primary school context. The study highlights the potential of ChatGPT in mathematics teaching and informs teacher education programs about the possibility of using it in teaching problem-solving strategies. DA - 2024/01/23/ PY - 2024 DO - 10.29333/iejme/14141 DP - DOI.org (Crossref) VL - 19 IS - 1 SP - em0766 J2 - INT ELECT J MATH ED SN - 1306-3030 ST - Pre-service teachers and ChatGPT in multistrategy problem-solving UR - https://www.iejme.com/article/pre-service-teachers-and-chatgpt-in-multistrategy-problem-solving-implications-for-mathematics-14141 Y2 - 2024/05/23/07:04:47 L1 - files/2848/Getenet - 2024 - Pre-service teachers and ChatGPT in multistrategy .pdf ER - TY - JOUR TI - Teachers’ readiness and intention to teach artificial intelligence in schools AU - Ayanwale, Musa Adekunle AU - Sanusi, Ismaila Temitayo AU - Adelana, Owolabi Paul AU - Aruleba, Kehinde D. AU - Oyelere, Solomon Sunday T2 - Computers and Education: Artificial Intelligence DA - 2022/// PY - 2022 DO - 10.1016/j.caeai.2022.100099 DP - DOI.org (Crossref) VL - 3 SP - 100099 J2 - Computers and Education: Artificial Intelligence LA - en SN - 2666920X UR - https://linkinghub.elsevier.com/retrieve/pii/S2666920X22000546 Y2 - 2023/05/26/10:58:40 L1 - files/3043/Ayanwale et al. - 2022 - Teachers’ readiness and intention to teach artific.pdf ER - TY - JOUR TI - National Council of Teachers of Mathematics AU - Leinwarnd, SE T2 - Principles ro actions: Ensuring Mathematical success for all. Reston: VA: Author DA - 2014/// PY - 2014 J2 - Principles ro actions: Ensuring Mathematical success for all. Reston: VA: Author ER - TY - CONF TI - AI chatbots as math algorithm problem solvers: A critical evaluation of its capabilities and limitations AU - Dahal, Niroj AU - Lamichhnae, BR AU - Luitel, Bal Chandra AU - Pant, Binod Prasad T2 - Proceedings of the 28th Asian Technology Conference in Mathematics DA - 2023/// PY - 2023 VL - 28 SP - 429 EP - 438 ER - TY - JOUR TI - Geometric Loci and ChatGPT: Caveat Emptor! AU - Botana, Francisco AU - Recio, Tomas T2 - Computation AB - We compare the performance of two systems, ChatGPT 3.5 and GeoGebra 5, in a restricted, but quite relevant, benchmark from the realm of classical geometry: the determination of geometric loci, focusing, in particular, on the computation of envelopes of families of plane curves. In order to study the loci calculation abilities of ChatGPT, we begin by entering an informal description of a geometric construction involving a locus or an envelope and then we ask ChatGPT to compute its equation. The chatbot fails in most situations, showing that it is not mature enough to deal with the subject. Then, the same constructions are also approached through the automated reasoning tools implemented in the dynamic geometry program, GeoGebra Discovery, which successfully resolves most of them. Furthermore, although ChatGPT is able to write general computer code, it cannot currently output that of GeoGebra. Thus, we consider describing a simple method for ChatGPT to generate GeoGebra constructions. Finally, in case GeoGebra fails, or gives an incorrect solution, we refer to the need for improved computer algebra algorithms to solve the loci/envelope constructions. Other than exhibiting the current problematic performance of the involved programs in this geometric context, our comparison aims to show the relevance and benefits of analyzing the interaction between them. DA - 2024/02/07/ PY - 2024 DO - 10.3390/computation12020030 DP - DOI.org (Crossref) VL - 12 IS - 2 SP - 30 J2 - Computation LA - en SN - 2079-3197 ST - Geometric Loci and ChatGPT UR - https://www.mdpi.com/2079-3197/12/2/30 Y2 - 2024/09/24/09:12:19 L1 - files/4946/Botana and Recio - 2024 - Geometric Loci and ChatGPT Caveat Emptor!.pdf ER - TY - JOUR TI - ChatGPT: A revolutionary tool for teaching and learning mathematics AU - Wardat, Yousef AU - Tashtoush, Mohammad A. AU - AlAli, Rommel AU - Jarrah, Adeeb M. T2 - Eurasia Journal of Mathematics, Science and Technology Education AB - This study aims to examine the perspectives of various stakeholders, such as students and educators, on the use of artificial intelligence in teaching mathematics, specifically after the launch of ChatGPT. The study adopts a qualitative case study approach consisting of two stages: content analysis of interviews and investigation of user experience. The first stage of the study shows that ChatGPT is recognized for its improved math capabilities and ability to increase educational success by providing users with basic knowledge of mathematics and various topics. ChatGPT can offer comprehensive instruction and assistance in the study of geometry, and the public discourse on social media is generally positive, with enthusiasm for the use of ChatGPT in teaching mathematics and educational settings. However, there are also voices that approach using ChatGPT in educational settings with caution. In the second stage of the study, the investigation of user experiences through three educational scenarios revealed various issues. ChatGPT lacks a deep understanding of geometry and cannot effectively correct misconceptions. The accuracy and effectiveness of ChatGPT solutions may depend on the complexity of the equation, input data, and the instructions given to ChatGPT. ChatGPT is expected to become more efficient in resolving increasingly complex mathematical problems. The results of this investigation propose a number of avenues for research that ought to be explored in order to guarantee the secure and conscientious integration of chatbots, especially ChatGPT, into mathematics education and learning. DA - 2023/07/01/ PY - 2023 DO - 10.29333/ejmste/13272 DP - DOI.org (Crossref) VL - 19 IS - 7 SP - em2286 J2 - EURASIA J Math Sci Tech Ed SN - 1305-8215, 1305-8223 ST - ChatGPT UR - https://www.ejmste.com/article/chatgpt-a-revolutionary-tool-for-teaching-and-learning-mathematics-13272 Y2 - 2024/09/24/09:28:06 L1 - files/4950/Wardat et al. - 2023 - ChatGPT A revolutionary tool for teaching and learning mathematics.pdf ER - TY - JOUR TI - Learning mathematics with large language models: A comparative study with computer algebra systems and other tools AU - Matzakos, Nikolaos AU - Doukakis, Spyridon AU - Moundridou, Maria T2 - International Journal of Emerging Technologies in Learning (iJET) DA - 2023/// PY - 2023 VL - 18 IS - 20 SP - 51 EP - 71 J2 - International Journal of Emerging Technologies in Learning (iJET) SN - 1863-0383 ER - TY - JOUR TI - Technological Pedagogical Content Knowledge: A Framework for Teacher Knowledge AU - Mishra, Punya AU - Koehler, Matthew J. T2 - Teachers College Record: The Voice of Scholarship in Education AB - Research in the area of educational technology has often been critiqued for a lack of theoretical grounding. In this article we propose a conceptual framework for educational technology by building on Shulrnan's formulation of “pedagogical content knowledge” and extend it to the phenomenon of teachers integrating technology into their pedagogy. This framework is the result of 5 years of work on a program of research focused on teacher professional development and faculty development in higher education. It attempts to capture some of the essential qualities of teacher knowledge required for technology integration in teaching, while addressing the complex, multifaceted, and situated nature of this knowledge. We argue, briefly, that thoughtful pedagogical uses of technology require the development of a complex, situated form of knowledge that we call Technological Pedagogical Content Knowledge (TPCK). In doing so, we posit the complex roles of, and interplay among, three main components of learning environments: content, pedagogy, and technology. We argue that this model has much to offer to discussions of technology integration at multiple levels: theoretical, pedagogical, and methodological. In this article, we describe the theory behind our framework, provide examples of our teaching approach based upon the framework, and illustrate the methodological contributions that have resulted from this work. DA - 2006/06// PY - 2006 DO - 10.1111/j.1467-9620.2006.00684.x DP - DOI.org (Crossref) VL - 108 IS - 6 SP - 1017 EP - 1054 J2 - Teachers College Record: The Voice of Scholarship in Education LA - en SN - 0161-4681, 1467-9620 ST - Technological Pedagogical Content Knowledge UR - https://journals.sagepub.com/doi/10.1111/j.1467-9620.2006.00684.x Y2 - 2024/11/01/14:03:58 ER - TY - JOUR TI - Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology AU - Davis, Fred D. T2 - MIS Quarterly DA - 1989/09// PY - 1989 DO - 10.2307/249008 DP - DOI.org (Crossref) VL - 13 IS - 3 SP - 319 J2 - MIS Quarterly SN - 02767783 UR - https://www.jstor.org/stable/249008?origin=crossref Y2 - 2025/01/04/18:15:08 ER - TY - JOUR TI - A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies AU - Venkatesh, Viswanath AU - Davis, Fred D. T2 - Management Science AB - The present research develops and tests a theoretical extension of the Technology Acceptance Model (TAM) that explains perceived usefulness and usage intentions in terms of social influence and cognitive instrumental processes. The extended model, referred to as TAM2, was tested using longitudinal data collected regarding four different systems at four organizations (N = 156), two involving voluntary usage and two involving mandatory usage. Model constructs were measured at three points in time at each organization: preimplementation, one month postimplementation, and three months postimplementation. The extended model was strongly supported for all four organizations at all three points of measurement, accounting for 40%–60% of the variance in usefulness perceptions and 34%–52% of the variance in usage intentions. Both social influence processes (subjective norm, voluntariness, and image) and cognitive instrumental processes (job relevance, output quality, result demonstrability, and perceived ease of use) significantly influenced user acceptance. These findings advance theory and contribute to the foundation for future research aimed at improving our understanding of user adoption behavior. DA - 2000/02// PY - 2000 DO - 10.1287/mnsc.46.2.186.11926 DP - DOI.org (Crossref) VL - 46 IS - 2 SP - 186 EP - 204 J2 - Management Science LA - en SN - 0025-1909, 1526-5501 ST - A Theoretical Extension of the Technology Acceptance Model UR - https://pubsonline.informs.org/doi/10.1287/mnsc.46.2.186.11926 Y2 - 2025/01/06/08:18:41 ER - TY - JOUR TI - Technology Acceptance Model 3 and a Research Agenda on Interventions AU - Venkatesh, Viswanath AU - Bala, Hillol T2 - Decision Sciences AB - ABSTRACT Prior research has provided valuable insights into how and why employees make a decision about the adoption and use of information technologies (ITs) in the workplace. From an organizational point of view, however, the more important issue is how managers make informed decisions about interventions that can lead to greater acceptance and effective utilization of IT. There is limited research in the IT implementation literature that deals with the role of interventions to aid such managerial decision making. Particularly, there is a need to understand how various interventions can influence the known determinants of IT adoption and use. To address this gap in the literature, we draw from the vast body of research on the technology acceptance model (TAM), particularly the work on the determinants of perceived usefulness and perceived ease of use, and: (i) develop a comprehensive nomological network (integrated model) of the determinants of individual level (IT) adoption and use; (ii) empirically test the proposed integrated model; and (iii) present a research agenda focused on potential pre‐ and postimplementation interventions that can enhance employees' adoption and use of IT. Our findings and research agenda have important implications for managerial decision making on IT implementation in organizations. DA - 2008/05// PY - 2008 DO - 10.1111/j.1540-5915.2008.00192.x DP - DOI.org (Crossref) VL - 39 IS - 2 SP - 273 EP - 315 J2 - Decision Sciences LA - en SN - 0011-7315, 1540-5915 UR - https://onlinelibrary.wiley.com/doi/10.1111/j.1540-5915.2008.00192.x Y2 - 2025/01/20/09:28:32 L1 - files/5042/Venkatesh and Bala - 2008 - Technology Acceptance Model 3 and a Research Agenda on Interventions.pdf ER - TY - JOUR TI - Back-Translation for Cross-Cultural Research AU - Brislin, Richard W. T2 - Journal of Cross-Cultural Psychology AB - Two aspects of translation were investigated: (1) factors that affect translation quality, and (2) how equivalence between source and target versions can be evaluated. The variables of language, content, and difficulty were studied through an analysis of variance design. Ninety-four bilinguals from the University of Guam, representing ten languages, translated or back-translated six essays incorporating three content areas and two levels of difficulty. The five criteria for equivalence were based on comparisons of meaning or predictions of similar responses to original or translated versions. The factors of content, difficulty, language and content-language interaction were significant, and the five equivalence criteria proved workable. Conclusions are that translation quality can be predicted, and that a functionally equivalent translation can be demonstrated when responses to the original and target versions are studied. DA - 1970/09// PY - 1970 DO - 10.1177/135910457000100301 DP - DOI.org (Crossref) VL - 1 IS - 3 SP - 185 EP - 216 J2 - Journal of Cross-Cultural Psychology LA - en SN - 0022-0221, 1552-5422 UR - https://journals.sagepub.com/doi/10.1177/135910457000100301 Y2 - 2025/01/26/17:47:57 ER - TY - JOUR TI - Enhancing mathematics teachers’ pedagogical skills by using ChatGPT AU - Alhazzani, Noura Saud T2 - International Journal of Innovative Research and Scientific Studies AB - The primary aim of this study was to propose a conceptual framework intended to leverage the capabilities of the Chat GPT artificial intelligence model to enhance the creative teaching proficiencies of secondary school mathematics teachers. A closed interview questionnaire designed by the researcher was administered to evaluate the proficiency levels of secondary mathematics teachers using a descriptive methodology. The study sample comprised 31 mathematics teachers. Furthermore, the researcher developed a proposed conceptual framework aimed at activating the Chat GPT model to foster creative teaching skills among secondary mathematics teachers. Analysis of the data revealed that teachers demonstrated a moderate level of proficiency in the planning dimension of creative teaching while their execution and evaluation competencies were comparatively less advanced. Moreover, the study confirmed the appropriateness of the proposed conceptual framework for augmenting the creative teaching aptitudes of secondary mathematics teachers emphasizing its relevance, significance and practical utility.  According to teachers’ perspectives, this framework is appropriate in light of its relevance, importance and applicability. In a nutshell, this research contributes to the discourse on innovative pedagogical strategies by proposing a viable framework for the integration of artificial intelligence technologies into mathematics education. By doing so, it seeks to nurture creativity and efficacy among teachers within the secondary school potentially enhancing the quality of mathematics instruction and student learning outcomes. These findings underscore the importance of integrating regenerative AI ChatGPT into classrooms emphasizing its role in enhancing creative teaching skills and its practical applicability in educational contexts. DA - 2024/08/23/ PY - 2024 DO - 10.53894/ijirss.v7i4.3460 DP - DOI.org (Crossref) VL - 7 IS - 4 SP - 1614 EP - 1626 J2 - ijirss SN - 2617-6548 UR - http://www.ijirss.com/index.php/ijirss/article/view/3460 Y2 - 2025/04/06/14:23:23 L1 - files/5083/Alhazzani - 2024 - Enhancing mathematics teachers’ pedagogical skills by using ChatGPT.pdf ER - TY - JOUR TI - Investigating the use of ChatGPT to solve a GeoGebra based mathematics+computational thinking task in a geometry topic AU - Yunianto, Wahid AU - Lavicza, Zsolt AU - Kastner-Hauler, Oliver AU - Houghton, Tony T2 - Journal on Mathematics Education AB - ChatGPT is a chatbot with potential educational benefits, particularly in enhancing computational thinking (CT) proficiencies such as programming, debugging, and algorithmic thinking for students. Despite its promise, there is limited research on how ChatGPT can specifically support the integration of CT into mathematics education using tools like GeoGebra. The researchers implemented plugged-computational thinking in mathematics (Math+CT) lessons by means of the utilization of GeoGebra, an application that requires students to input commands in order to generate mathematical objects. The present investigation employed an educational design research (EDR) methodology in which the researchers incorporate ChatGPT into our Math+CT lessons to assist students in accomplishing the task. We purposely selected the participants who are mainly postgraduate students and collected data from the participants’ conversation with ChatGPT and recorded their screens while interacting with ChatGPT and our Math+CT task. We analyzed the data through descriptive qualitative method on the participants’ prompts, the final codes and the number of iterations. The researchers examined how ChatGPT could be utilized to assist the participants in writing GeoGebra commands in terms of its benefits and limitations. ChatGPT assisted most participants in completing the task successfully, with only a basic need for proficiency in GeoGebra commands, mathematics, and critical thinking. However, it revealed that participants did not yet utilize an affective prompt to ChatGPT. Furthermore, ChatGPT has the potential to be utilized for differentiated instruction due to the fact that its responses to individual users vary significantly based on the input prompts. Limited understanding of basic GeoGebra commands, and mathematical concepts could hinder the participants from training ChatGPT or prevent them from arguing with ChatGPT. This study enhances the existing literature by illustrating that ChatGPT can facilitate critical CT aspects, including programming and debugging, in a mathematics education context. This suggests that AI tools such as ChatGPT can contribute to the development of independent problem-solving skills, provide tailored support based on the needs of individual students, and enhance personalized learning experiences. Additional research involving students in school is required in order to gain a deeper understanding of the integration of ChatGPT into Math+CT lessons. DA - 2024/09/06/ PY - 2024 DO - 10.22342/jme.v15i3.pp1027-1052 DP - DOI.org (Crossref) VL - 15 IS - 3 SP - 1027 EP - 1052 J2 - j. math. educ. SN - 2407-0610, 2087-8885 UR - http://jme.ejournal.unsri.ac.id/index.php/jme/article/view/726 Y2 - 2025/04/08/13:11:51 ER - TY - JOUR TI - Pre-Service Teachers’ Approaches in Solving Mathematics Tasks with ChatGPT AU - Noster, Norbert AU - Gerber, Sebastian AU - Siller, Hans-Stefan T2 - Digital Experiences in Mathematics Education AB - Abstract The use of large language models like ChatGPT is widely discussed for educational purposes. Using this technology requires teachers to have appropriate competences that incorporate knowledge of how to make use of this technology. In this study, we investigate pre-service teachers’ knowledge through the lens of the KTMT model (“Knowledge for Teaching Mathematics with Technology” model), a domain-specific variant of the TPACK-model. One component is represented in mathematical fidelity as knowledge of the mathematical accuracy of the technology, which in case of large language models is of special interest, as it may produce erroneous but plausible-sounding information. Furthermore, prompting techniques are of interest as technological knowledge, which influence mathematical fidelity. For this study, eleven pre-service teachers were asked to solve four different mathematical tasks with the help of ChatGPT. The chatlogs and information provided in an interview after working on the tasks are analyzed using qualitative content analysis. Results show that both correct and incorrect answers were produced for all tasks. The rate of pre-service teachers providing an incorrect answer is high when having been presented with an incorrect answer generated by the large language model. Despite having access to ChatGPT as a tool, many of the participants were not able to provide correct answers to all tasks. Furthermore, the mathematical fidelity was often over- and, in some cases, underrated. The mathematical knowledge seems to have changed while working with ChatGPT. Based on the applied prompting techniques, the pre-service teachers showed a deficiency in technological knowledge. DA - 2024/12// PY - 2024 DO - 10.1007/s40751-024-00155-8 DP - DOI.org (Crossref) VL - 10 IS - 3 SP - 543 EP - 567 J2 - Digit Exp Math Educ LA - en SN - 2199-3246, 2199-3254 UR - https://link.springer.com/10.1007/s40751-024-00155-8 Y2 - 2025/04/08/13:17:05 L1 - files/5095/Noster et al. - 2024 - Pre-Service Teachers’ Approaches in Solving Mathematics Tasks with ChatGPT.pdf ER - TY - JOUR TI - ChatGPT in education: benefits and challenges of ChatGPT for mathematics and science teaching practices AU - Taani, Osama AU - Alabidi, Suzan T2 - International Journal of Mathematical Education in Science and Technology DA - 2024/05/28/ PY - 2024 DO - 10.1080/0020739X.2024.2357341 DP - DOI.org (Crossref) SP - 1 EP - 30 J2 - International Journal of Mathematical Education in Science and Technology LA - en SN - 0020-739X, 1464-5211 ST - ChatGPT in education UR - https://www.tandfonline.com/doi/full/10.1080/0020739X.2024.2357341 Y2 - 2025/04/09/14:34:57 ER - TY - JOUR TI - Teachers’ Beliefs and Practices About the Potential of ChatGPT in Teaching Mathematics in Secondary Schools AU - Busuttil, Leonard AU - Calleja, James T2 - Digital Experiences in Mathematics Education AB - Abstract This study investigates the beliefs and practices of secondary school mathematics teachers in Malta regarding the potential of generative artificial intelligence (GenAI), particularly through tools like ChatGPT, in teaching, using the TPACK framework. Through a case study methodology involving pre- and post-professional development (PD) session surveys and analysis of field notes, the research examines the alignment between teachers’ self-reported beliefs and pedagogical practices and their perceptions of ChatGPT’s utility. Findings show teachers, particularly those with discovery and connectionist educational philosophies, view ChatGPT positively, believing it fosters active learning, encourages exploration, and supports individualised engagement. Despite challenges like interpreting visual mathematical representations and inaccuracies, teachers see ChatGPT as a tool for creating practice problems, assessments, and personalised feedback, aligning with trends in existing literature. The study underscores the necessity of ongoing PD to equip teachers with the skills to integrate ChatGPT effectively into their pedagogy, suggesting a deeper understanding of both the opportunities and challenges presented by GenAI in education. The alignment of teachers’ beliefs and practices with their perceptions of ChatGPT’s potential suggests a readiness among educators to adopt innovative technologies that align with contemporary pedagogical values, enhancing the teaching and learning experience in mathematics. This research contributes to the body of knowledge on GenAI integration in education, highlighting the importance of aligning educational technology with teachers’ pedagogical beliefs and practices to maximise its benefits and recognising the potential of ChatGPT to change mathematics education by facilitating active engagement and personalised learning, while also acknowledging its limitations and ethical implications. DA - 2025/04// PY - 2025 DO - 10.1007/s40751-024-00168-3 DP - DOI.org (Crossref) VL - 11 IS - 1 SP - 140 EP - 166 J2 - Digit Exp Math Educ LA - en SN - 2199-3246, 2199-3254 UR - https://link.springer.com/10.1007/s40751-024-00168-3 Y2 - 2025/04/11/13:15:01 L1 - files/5099/Busuttil and Calleja - 2025 - Teachers’ Beliefs and Practices About the Potential of ChatGPT in Teaching Mathematics in Secondary.pdf ER - TY - JOUR TI - Using ChatGPT as a Lesson Planning Assistant with Preservice Secondary Mathematics Teachers AU - Gurl, Theresa J. AU - Markinson, Mara P. AU - Artzt, Alice F. T2 - Digital Experiences in Mathematics Education DA - 2025/04// PY - 2025 DO - 10.1007/s40751-024-00162-9 DP - DOI.org (Crossref) VL - 11 IS - 1 SP - 114 EP - 139 J2 - Digit Exp Math Educ LA - en SN - 2199-3246, 2199-3254 UR - https://link.springer.com/10.1007/s40751-024-00162-9 Y2 - 2025/04/11/17:49:04 L1 - files/5102/Gurl et al. - 2025 - Using ChatGPT as a Lesson Planning Assistant with Preservice Secondary Mathematics Teachers.pdf ER - TY - JOUR TI - Learning to Craft and Critically Evaluate Prompts: The Role of Generative AI (ChatGPT) in Enhancing Pre-service Mathematics Teachers' TPACK and Problem-Posing Skills AU - Biton, Yaniv AU - Segal, Ruti T2 - International Journal of Education in Mathematics, Science and Technology AB - The use of generative AI (Chat GPT) for the process of posing mathematical problems was introduced to 15 pre-service teachers (henceforth referred to as "teachers") in a re-training program aimed at teaching advanced secondary school mathematics. After solving mathematical problems, they were given an assignment to pose and refine additional problems in accordance with the curriculum requirements by giving "prompts" to the AI environment and refining them as needed. In this paper, we focus on the qualitative analysis of three key stages experienced by the teachers: writing the initial prompt to request assistance from ChatGPT to improve the problem; the response provided by ChatGPT; and the teachers' reflections on how they utilized ChatGPT's recommendations to update and refine their problem. This analysis reveals that the chat's responses and the teachers' reactions to them made several key contributions to improving mathematical problems, particularly by enhancing the clarity of the problem and increasing its challenge and complexity. Additionally, it improved mathematical precision and showed how it could be linked to real-world applications, thereby increasing student engagement. The chat also encouraged inquiry-based thinking and provided guidance for helping struggling students. Overall, these contributions significantly enhanced the quality of the mathematical problems and improved their TPACK (theoretical, pedagogical, and content knowledge). DA - 2025/01/27/ PY - 2025 DO - 10.46328/ijemst.4654 DP - DOI.org (Crossref) VL - 13 IS - 1 SP - 202 EP - 223 J2 - IJEMST SN - 2147-611X ST - Learning to Craft and Critically Evaluate Prompts UR - https://ijemst.net/index.php/ijemst/article/view/4654 Y2 - 2025/04/11/18:03:15 L1 - files/5104/Biton and Segal - 2025 - Learning to Craft and Critically Evaluate Prompts The Role of Generative AI (ChatGPT) in Enhancing.pdf ER - TY - JOUR TI - AI ChatBots’ solutions to mathematical problems in interactive e-textbooks: Affordances and constraints from the eyes of students and teachers AU - Ergene, Ozkan AU - Ergene, Busra Caylan T2 - Education and Information Technologies DA - 2025/01// PY - 2025 DO - 10.1007/s10639-024-13121-z DP - DOI.org (Crossref) VL - 30 IS - 1 SP - 509 EP - 545 J2 - Educ Inf Technol LA - en SN - 1360-2357, 1573-7608 ST - AI ChatBots’ solutions to mathematical problems in interactive e-textbooks UR - https://link.springer.com/10.1007/s10639-024-13121-z Y2 - 2025/04/14/08:06:00 ER - TY - JOUR TI - Investigating the Role of ChatGPT in Supporting Metacognitive Processes During Problem-Solving Activities AU - Contel, Francesco AU - Cusi, Annalisa T2 - Digital Experiences in Mathematics Education DA - 2025/04// PY - 2025 DO - 10.1007/s40751-024-00164-7 DP - DOI.org (Crossref) VL - 11 IS - 1 SP - 167 EP - 191 J2 - Digit Exp Math Educ LA - en SN - 2199-3246, 2199-3254 UR - https://link.springer.com/10.1007/s40751-024-00164-7 Y2 - 2025/04/14/08:19:15 ER - TY - JOUR TI - Exploring the integration of artificial intelligence in math education: Preservice Teachers’ experiences and reflections on problem‐posing activities with ChatGPT AU - Kim, Young Rae AU - Park, Mi Sun AU - Joung, Eunmi T2 - School Science and Mathematics AB - Abstract This study addresses the need for research that incorporates educational perspectives and theories to understand the impact of Artificial Intelligence (AI) on learning and teaching. Utilizing AI‐integrated mathematical problem‐posing (AIM) activities and the AI‐powered scaffolding (AIS) strategy, the research investigated preservice teachers’ (PTs’) experiences with AI and their capacity for error recognition and correction in problems posed by ChatGPT. The findings reveal that while the PTs excelled at verifying error‐free problems, they struggled significantly with identifying and correcting errors, indicating a gap in their instructional preparedness. The study demonstrates that AIM activities are effective tools for assessing and developing PTs’ error recognition and correction skills. Additionally, AIM activities support the transfer of mathematical knowledge to pedagogical and instructional practices, contributing to PTs’ growth as adaptable educators. The research highlights the need to integrate AI‐based activities into PT training to build robust mathematical knowledge and teaching skills. Focusing on learning, pedagogy, and the human aspects of technology use, AIM activities and the AIS strategy enable PTs to engage critically with AI outputs and enhance their metacognitive skills. These insights emphasize the importance of incorporating AI‐integrated methods into teacher preparation programs to better equip future educators for an AI‐driven educational landscape. DA - 2025/01/27/ PY - 2025 DO - 10.1111/ssm.18336 DP - DOI.org (Crossref) SP - ssm.18336 J2 - School Sci & Mathematics LA - en SN - 0036-6803, 1949-8594 ST - Exploring the integration of artificial intelligence in math education UR - https://onlinelibrary.wiley.com/doi/10.1111/ssm.18336 Y2 - 2025/04/14/10:50:32 ER - TY - JOUR TI - Students’ use of generative artificial intelligence for proving mathematical statements AU - Yoon, Hyunkyoung AU - Hwang, Jihye AU - Lee, Kyungwon AU - Roh, Kyeong Hah AU - Kwon, Oh Nam T2 - ZDM – Mathematics Education AB - Abstract In this exploratory study, we investigate undergraduate students’ engagement with generative Artificial Intelligence (genAI) in proving mathematical statements. We selected six mathematical statements to conduct interviews with three students. We present the emergent framework, Students’ Interactive Proving Experience with AI (SIPE-AI), which explains the processes of students’ use of genAI in their proving and the factors influencing these processes. Our findings identify three factors that shape students’ use of genAI: conceptions of proof, conceptions of genAI, and ethical considerations. The results suggest a need to guide undergraduate students in critically engaging with genAI tools, rather than passively accepting their outputs. We also discuss the implications of these findings for enhancing undergraduate mathematics education by fostering informed and critical use of genAI in mathematical proving. DA - 2024/12// PY - 2024 DO - 10.1007/s11858-024-01629-0 DP - DOI.org (Crossref) VL - 56 IS - 7 SP - 1531 EP - 1551 J2 - ZDM Mathematics Education LA - en SN - 1863-9690, 1863-9704 UR - https://link.springer.com/10.1007/s11858-024-01629-0 Y2 - 2025/04/14/11:46:25 L1 - files/5114/Yoon et al. - 2024 - Students’ use of generative artificial intelligence for proving mathematical statements.pdf ER - TY - CONF TI - Use of Game-Based Learning with ChatGPT to Improve Mathematical Modeling Competences in First-Year Engineering Students AU - Sayeg-Sánchez, Gibrán AU - Rodriguez-Paz, Miguel X T2 - 2024 ASEE Annual Conference & Exposition DA - 2024/// PY - 2024 ER - TY - JOUR TI - It’s not like a calculator, so what is the relationship between learners and generative artificial intelligence? AU - Lodge, Jason M. AU - Yang, Suijing AU - Furze, Leon AU - Dawson, Phillip T2 - Learning: Research and Practice DA - 2023/07/03/ PY - 2023 DO - 10.1080/23735082.2023.2261106 DP - DOI.org (Crossref) VL - 9 IS - 2 SP - 117 EP - 124 J2 - Learning: Research and Practice LA - en SN - 2373-5082, 2373-5090 UR - https://www.tandfonline.com/doi/full/10.1080/23735082.2023.2261106 Y2 - 2025/04/29/07:37:03 ER - TY - JOUR TI - TPACK in the age of ChatGPT and Generative AI AU - Mishra, Punya AU - Warr, Melissa AU - Islam, Rezwana T2 - Journal of Digital Learning in Teacher Education DA - 2023/10/02/ PY - 2023 DO - 10.1080/21532974.2023.2247480 DP - DOI.org (Crossref) VL - 39 IS - 4 SP - 235 EP - 251 J2 - Journal of Digital Learning in Teacher Education LA - en SN - 2153-2974, 2332-7383 UR - https://www.tandfonline.com/doi/full/10.1080/21532974.2023.2247480 Y2 - 2025/04/29/07:37:45 ER - TY - JOUR TI - An Updated and Streamlined Technology Readiness Index: TRI 2.0 AU - Parasuraman, A. AU - Colby, Charles L. T2 - Journal of Service Research AB - The Technology Readiness Index (TRI), a 36-item scale to measure people’s propensity to embrace and use cutting-edge technologies, was published in the Journal of Service Research over a decade ago. Researchers have since used it in a variety of contexts in over two dozen countries. Meanwhile, several revolutionary technologies (mobile commerce, social media, and cloud computing) that were in their infancy just a decade ago are now pervasive and significantly impacting people’s lives. Based on insights from extensive experience with the TRI and given the significant changes in the technology landscape, the authors undertook a two-phase research project to update and streamline the TRI. After providing a brief overview of technology readiness and the original TRI, this article (a) describes the multiple research stages and analyses that produced TRI 2.0, a 16-item scale; (b) compares TRI 2.0 with the original TRI in terms of content, structure, and psychometric properties; and (c) demonstrates TRI 2.0’s reliability, validity, and usefulness as a customer segmentation tool. The article concludes with potential applications of TRI 2.0 and directions for future research. DA - 2015/02// PY - 2015 DO - 10.1177/1094670514539730 DP - DOI.org (Crossref) VL - 18 IS - 1 SP - 59 EP - 74 J2 - Journal of Service Research LA - en SN - 1094-6705, 1552-7379 ST - An Updated and Streamlined Technology Readiness Index UR - https://journals.sagepub.com/doi/10.1177/1094670514539730 Y2 - 2025/04/29/07:39:45 ER - TY - JOUR TI - Your Prompt is My Command: On Assessing the Human-Centred Generality of Multimodal Models AU - Schellaert, Wout AU - Martínez-Plumed, Fernando AU - Vold, Karina AU - Burden, John AU - A. M. Casares, Pablo AU - Sheng Loe, Bao AU - Reichart, Roi AU - Ó hÉigeartaigh, Sean AU - Korhonen, Anna AU - Hernández-Orallo, José T2 - Journal of Artificial Intelligence Research AB - Even with obvious deficiencies, large prompt-commanded multimodal models are proving to be flexible cognitive tools representing an unprecedented generality. But the directness, diversity, and degree of user interaction create a distinctive “human-centred generality” (HCG), rather than a fully autonomous one. HCG implies that —for a specific user— a system is only as general as it is effective for the user’s relevant tasks and their prevalent ways of prompting. A human-centred evaluation of general-purpose AI systems therefore needs to reflect the personal nature of interaction, tasks and cognition. We argue that the best way to understand these systems is as highly-coupled cognitive extenders, and to analyse the bidirectional cognitive adaptations between them and humans. In this paper, we give a formulation of HCG, as well as a high-level overview of the elements and trade-offs involved in the prompting process. We end the paper by outlining some essential research questions and suggestions for improving evaluation practices, which we envision as characteristic for the evaluation of general artificial intelligence in the future. This paper appears in the AI & Society track. DA - 2023/06/12/ PY - 2023 DO - 10.1613/jair.1.14157 DP - DOI.org (Crossref) VL - 77 SP - 377 EP - 394 J2 - jair SN - 1076-9757 ST - Your Prompt is My Command UR - http://jair.org/index.php/jair/article/view/14157 Y2 - 2025/04/29/07:40:30 L1 - files/5200/Schellaert et al. - 2023 - Your Prompt is My Command On Assessing the Human-Centred Generality of Multimodal Models.pdf ER - TY - GEN TI - Advice on AI, Chatbots and similar tools DA - 2024/// PY - 2024 LA - Swedish PB - Skolverket UR - https://www.skolverket.se/skolutveckling/inspiration-och-stod-i-arbetet/stod-i-arbetet/rad-om-ai-chattbottar-och-liknande-verktyg Y2 - 2025/05/10/ ER - TY - CONF TI - ChatGPT in education: Teachers’ and Students’ views AU - Söderström, Ulrik AU - Hedström, Elsa AU - Lambertsson, Karl AU - Mejtoft, Thomas T2 - ECCE 2024: European Conference on Cognitive Ergonomics C1 - Paris France C3 - Proceedings of the European Conference on Cognitive Ergonomics 2024 DA - 2024/10/08/ PY - 2024 DO - 10.1145/3673805.3673828 DP - DOI.org (Crossref) SP - 1 EP - 10 LA - en PB - ACM SN - 979-8-4007-1824-3 ST - ChatGPT in education UR - https://dl.acm.org/doi/10.1145/3673805.3673828 Y2 - 2025/05/10/17:40:37 L1 - files/5228/Söderström et al. - 2024 - ChatGPT in education Teachers’ and Students’ views.pdf ER - TY - JOUR TI - What is technological pedagogical content knowledge (TPACK)? AU - Koehler, Matthew AU - Mishra, Punya T2 - Contemporary issues in technology and teacher education DA - 2009/// PY - 2009 VL - 9 IS - 1 SP - 60 EP - 70 J2 - Contemporary issues in technology and teacher education SN - 1528-5804 ER - TY - JOUR TI - Preparing teachers to teach science and mathematics with technology: Developing a technology pedagogical content knowledge AU - Niess, M.L. T2 - Teaching and Teacher Education DA - 2005/07// PY - 2005 DO - 10.1016/j.tate.2005.03.006 DP - DOI.org (Crossref) VL - 21 IS - 5 SP - 509 EP - 523 J2 - Teaching and Teacher Education LA - en SN - 0742051X ST - Preparing teachers to teach science and mathematics with technology UR - https://linkinghub.elsevier.com/retrieve/pii/S0742051X05000387 Y2 - 2025/05/10/19:16:07 ER - TY - JOUR TI - Towards Intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education AU - Celik, Ismail T2 - Computers in Human Behavior DA - 2023/01// PY - 2023 DO - 10.1016/j.chb.2022.107468 DP - DOI.org (Crossref) VL - 138 SP - 107468 J2 - Computers in Human Behavior LA - en SN - 07475632 ST - Towards Intelligent-TPACK UR - https://linkinghub.elsevier.com/retrieve/pii/S0747563222002886 Y2 - 2025/05/11/11:11:44 L1 - files/5236/Celik - 2023 - Towards Intelligent-TPACK An empirical study on teachers’ professional knowledge to ethically integ.pdf ER - TY - JOUR TI - Attitudes, perceptions and AI self-efficacy in K-12 education AU - Bergdahl, Nina AU - Sjöberg, Jeanette T2 - Computers and Education: Artificial Intelligence DA - 2025/06// PY - 2025 DO - 10.1016/j.caeai.2024.100358 DP - DOI.org (Crossref) VL - 8 SP - 100358 J2 - Computers and Education: Artificial Intelligence LA - en SN - 2666920X UR - https://linkinghub.elsevier.com/retrieve/pii/S2666920X24001619 Y2 - 2025/05/12/09:53:55 ER - TY - JOUR TI - Beginning and first-year language teachers’ readiness for the generative AI age AU - Moorhouse, Benjamin Luke T2 - Computers and Education: Artificial Intelligence DA - 2024/06// PY - 2024 DO - 10.1016/j.caeai.2024.100201 DP - DOI.org (Crossref) VL - 6 SP - 100201 J2 - Computers and Education: Artificial Intelligence LA - en SN - 2666920X UR - https://linkinghub.elsevier.com/retrieve/pii/S2666920X2400002X Y2 - 2025/05/20/09:14:40 ER - TY - JOUR TI - Exploring In-service EFL Teachers’ Readiness for the Generative AI Age AU - Ozdemir, Nihal AU - Mede, Enisa T2 - International Journal of Research in Teacher Education DA - 2024/11/29/ PY - 2024 DP - DOI.org (Crossref) VL - 15 IS - 5 J2 - IJRTE SN - 1308-951X ER - TY - JOUR TI - Generational attitudes and teacher ICT use AU - Pegler, Karen AU - Kollewyn, Joan AU - CriChton, SuSan T2 - Journal of Technology and Teacher Education DA - 2010/// PY - 2010 VL - 18 IS - 3 SP - 443 EP - 458 J2 - Journal of Technology and Teacher Education SN - 1059-7069 ER - TY - JOUR TI - Generational Differences in Faculty and Student Comfort With Technology Use AU - Culp-Roche, Amanda AU - Hampton, Debra AU - Hensley, Angie AU - Wilson, Jessica AU - Thaxton-Wiggins, Amanda AU - Otts, Jo Ann AU - Fruh, Sharon AU - Moser, Debra K. T2 - SAGE Open Nursing AB - Background Navigating through online education courses continues to be a struggle for some nursing students. At the same time, integrating technology into online courses can be difficult for nursing faculty. Purpose The purpose of this study was to assess faculty technology integration practices, student attitudes about technology use, and generational differences related to faculty and student technology use. Methods A descriptive cross-sectional survey design was used to obtain data for this study. Results Integration of technology into online courses and student attitudes about technology use were not significantly different by generation. Faculty and students from the Baby Boomer and Generation X reported less comfort using technology and higher levels of anxiety using technology than did individuals from Generation Y. Conclusion Significant generational variations were not noted in relation to technology integration into courses and overall student attitudes about technology in this study, but differences were noted in relation to comfort with use of technology and anxiety when using technology. Student learning outcomes and satisfaction with learning may be influenced by the student’s comfort using technology and faculty’s confidence in integrating and using technology to provide online instruction. DA - 2020/01// PY - 2020 DO - 10.1177/2377960820941394 DP - DOI.org (Crossref) VL - 6 SP - 2377960820941394 J2 - SAGE Open Nursing LA - en SN - 2377-9608, 2377-9608 UR - https://journals.sagepub.com/doi/10.1177/2377960820941394 Y2 - 2025/05/25/07:17:13 L1 - files/5246/Culp-Roche et al. - 2020 - Generational Differences in Faculty and Student Comfort With Technology Use.pdf ER - TY - CHAP TI - Calculators in Mathematics Education: A Rapid Evolution of Tools, with Differential Effects AU - Trouche, Luc T2 - The Didactical Challenge of Symbolic Calculators A2 - Guin, Dominique A2 - Ruthven, Kenneth A2 - Trouche, Luc CY - New York DA - 2005/// PY - 2005 DP - DOI.org (Crossref) VL - 36 SP - 9 EP - 39 LA - en PB - Springer-Verlag SN - 978-0-387-23158-7 ST - Calculators in Mathematics Education UR - http://link.springer.com/10.1007/0-387-23435-7_2 Y2 - 2025/05/25/07:31:13 ER - TY - JOUR TI - Exploring insights from online students: Enhancing the design and development of intelligent textbooks for the future of online education AU - Lee, Jeonghyun AU - Soylu, Meryem Yilmaz AU - Ou, Chaohua T2 - International Journal on Innovations in Online Education AB - The global pandemic accelerated the shift to remote teaching, leading to a rise in digital course materials such as textbooks. However, existing literature indicates that there is limited research on how online students utilize digital textbooks as well as on the features they find valuable for their online learning experiences and desire to aid their learning. Therefore, the purpose of this research was to explore the experiences and perceptions among diverse online students and then draw implications for the design of future intelligent textbooks. This study surveyed online degree-seeking students (n = 1236) from three different institutions in the United States in 2022. Based on the mixed-method research design, this exploratory study used qualitative data from open-ended questions and quantitative data from closed-ended questions to theme patterns of response. The results indicated that most participants have used at least one digital textbook, and in general they were familiar with such features as searching, visuals, and embedded assessments. These features, associated with self-directed and multimedia learning, received more positive ratings compared to adaptive or personalized learning features such as chatbots and recommended content. In the findings of the study, surveyed participants described future intelligent digital textbooks to be ideal for self-directed learning, since they can accommodate diverse learning needs and are flexible and affordable. Overall, this study provides insights into future intelligent textbooks and other digital materials as a comprehensive learning system and supports their use for empowering online learners to go beyond text-based learning and enhancing their digital learning experience. DA - 2023/// PY - 2023 DO - 10.1615/IntJInnovOnlineEdu.2023049742 DP - DOI.org (Crossref) VL - 7 IS - 2 SP - 29 EP - 55 J2 - Int J Innov Online Edu LA - en SN - 2377-9519 UR - https://onlineinnovationsjournal.com/streams/assessments/4a7580ab6bfc7fdb.html Y2 - 2025/05/25/07:32:06 ER - TY - CHAP TI - Learning Management Systems (LMSs) AU - Lang, Susan T2 - Digital Writing Technologies in Higher Education A2 - Kruse, Otto A2 - Rapp, Christian A2 - Anson, Chris M. A2 - Benetos, Kalliopi A2 - Cotos, Elena A2 - Devitt, Ann A2 - Shibani, Antonette AB - Abstract This chapter provides a brief overview of the history of Learning Management Systems before turning to those currently in widespread use. While surveying these systems, the chapter will focus on the extent of the ability of these platforms to contribute to writing instruction, writing analytics, and learning analytics. It will also discuss the development of LMSs designed specifically for writing instruction. CY - Cham DA - 2023/// PY - 2023 DP - DOI.org (Crossref) SP - 173 EP - 182 LA - en PB - Springer International Publishing SN - 978-3-031-36032-9 978-3-031-36033-6 UR - https://link.springer.com/10.1007/978-3-031-36033-6_11 Y2 - 2025/05/25/07:32:52 L1 - files/5250/Lang - 2023 - Learning Management Systems (LMSs).pdf ER - TY - JOUR TI - TPACK in context: An updated model AU - Petko, Dominik AU - Mishra, Punya AU - Koehler, Matthew J T2 - Computers and Education Open DA - 2025/06// PY - 2025 DO - 10.1016/j.caeo.2025.100244 DP - DOI.org (Crossref) VL - 8 SP - 100244 J2 - Computers and Education Open LA - en SN - 26665573 ST - TPACK in context UR - https://linkinghub.elsevier.com/retrieve/pii/S2666557325000035 Y2 - 2025/05/27/12:05:31 ER - TY - JOUR TI - Investigating TPACK: Knowledge Growth in Teaching with Technology AU - Niess, Margaret L. T2 - Journal of Educational Computing Research AB - Technological pedagogical and content knowledge (TPACK) presents a dynamic framework for describing teachers' knowledge required for designing, implementing, and evaluating curriculum and instruction with technology. TPACK strategic thinking includes knowing when, where, and how to use domain-specific knowledge and strategies for guiding students' learning with appropriate information and communication technologies. Multiple visual and verbal descriptions reflect evolving recognitions of teacher educators and educational researchers as they have struggled to respond to the challenges in describing and developing teachers' TPACK. This extensive reflection maps the historical acceptance of pedagogical content knowledge (PCK) with the emerging views of and challenges with TPACK. A review of empirical progress in the investigation of TPACK serves to illuminate potential insights, values, and challenges for directing future educational implementations designed to identify a teacher's learning trajectory in the development of a more robust and mature TPACK for supporting them in teaching with current and emerging technologies. DA - 2011/04// PY - 2011 DO - 10.2190/EC.44.3.c DP - DOI.org (Crossref) VL - 44 IS - 3 SP - 299 EP - 317 J2 - Journal of Educational Computing Research LA - en SN - 0735-6331, 1541-4140 ST - Investigating TPACK UR - https://journals.sagepub.com/doi/10.2190/EC.44.3.c Y2 - 2025/05/27/12:08:02 ER - TY - JOUR TI - Exploring teachers’ pedagogical reasoning in mathematics education using the TPACK framework AU - Priyanda, Roni AU - Herman, Tatang AU - Amalia, Rizki AU - Ihsan, Iden Rainal T2 - Frontiers in Education AB - Effective integration of technology in mathematics education requires teachers to blend content knowledge, pedagogical strategies, and digital tools. The Technological Pedagogical Content Knowledge (TPACK) framework offers a lens for understanding teachers’ pedagogical reasoning when designing technology-enhanced lessons. However, the ways in which TPACK informs instructional planning and the challenges educators face remain under - synthesized. A systematic review following PRISMA guidelines was conducted using Scopus (2015–2024). Search terms included “pedagogical reasoning,” “instructional reasoning,” “TPACK,” and “math*.” From 118 records retrieved, title/abstract screening and full - text eligibility assessments yielded eight empirical studies examining TPACK and pedagogical reasoning in mathematics contexts. The included studies employed predominantly qualitative case studies and mixed - methods designs to capture teachers’ decision - making processes. Findings indicate that educators leverage TPACK to enhance conceptual understanding and student engagement via dynamic visualizations, interactive simulations, and scaffolded digital tasks. Common obstacles include limited subject - specific professional development, resource constraints, and heterogeneity in teachers’ TPACK proficiency. Evidence also highlights TPACK’s capacity to foster inquiry - based learning and develop teachers’ adaptive expertise. Sustained, targeted professional development and equitable access to technology are essential for deepening TPACK enactment. Implications for practice include designing PD programs that integrate subject - specific technology applications and creating institutional support structures. Future research should investigate longitudinal impacts of TPACK on teachers’ reflective practices and student outcomes, and develop standardized assessment tools tailored to mathematics instruction. DA - 2025/05/16/ PY - 2025 DO - 10.3389/feduc.2025.1552760 DP - DOI.org (Crossref) VL - 10 SP - 1552760 J2 - Front. Educ. SN - 2504-284X UR - https://www.frontiersin.org/articles/10.3389/feduc.2025.1552760/full Y2 - 2025/05/27/12:09:14 ER - TY - JOUR TI - A Scoping Survey of ChatGPT in Mathematics Education AU - Pepin, Birgit AU - Buchholtz, Nils AU - Salinas-Hernández, Ulises T2 - Digital Experiences in Mathematics Education AB - Abstract This study presents a scoping survey examining the integration of ChatGPT in mathematics education, highlighting its benefits, challenges, and implications for teaching and learning. The survey identifies key themes, including ChatGPT’s ability to assist in understanding mathematical concepts, lesson planning, assessment design, personalized learning, and fostering collaboration. While the tool demonstrates potential in enhancing self-regulated learning, providing real-time feedback, and supporting critical thinking, challenges such as its occasional inaccuracies, ethical concerns, and the risk of over-reliance on AI are also noted. The review emphasizes the importance of human oversight and ethical considerations in leveraging ChatGPT for inclusive and dynamic mathematics education. It concludes that, with thoughtful integration, ChatGPT can serve as a transformative resource, fostering both individualized and collaborative learning experiences while reshaping the learner–tool relationship in educational contexts. DA - 2025/04// PY - 2025 DO - 10.1007/s40751-025-00172-1 DP - DOI.org (Crossref) VL - 11 IS - 1 SP - 9 EP - 41 J2 - Digit Exp Math Educ LA - en SN - 2199-3246, 2199-3254 UR - https://link.springer.com/10.1007/s40751-025-00172-1 Y2 - 2025/05/29/11:12:27 L1 - files/5256/Pepin et al. - 2025 - A Scoping Survey of ChatGPT in Mathematics Education.pdf ER - TY - RPRT TI - GPT-4 AU - OpenAI T2 - Milestones DA - 2023/03/14/ PY - 2023 LA - English UR - https://openai.com/index/gpt-4-research/ Y2 - 2025/06/04/ ER - TY - JOUR TI - The promise and challenges of generative AI in education AU - Giannakos, Michail AU - Azevedo, Roger AU - Brusilovsky, Peter AU - Cukurova, Mutlu AU - Dimitriadis, Yannis AU - Hernandez-Leo, Davinia AU - Järvelä, Sanna AU - Mavrikis, Manolis AU - Rienties, Bart T2 - Behaviour & Information Technology DA - 2024/09/02/ PY - 2024 DO - 10.1080/0144929X.2024.2394886 DP - DOI.org (Crossref) SP - 1 EP - 27 J2 - Behaviour & Information Technology LA - en SN - 0144-929X, 1362-3001 UR - https://www.tandfonline.com/doi/full/10.1080/0144929X.2024.2394886 Y2 - 2025/06/06/17:54:08 L1 - files/5261/Giannakos et al. - 2024 - The promise and challenges of generative AI in education.pdf ER - TY - JOUR TI - Considering Contextual Knowledge: The TPACK Diagram Gets an Upgrade AU - Mishra, Punya T2 - Journal of Digital Learning in Teacher Education DA - 2019/04/03/ PY - 2019 DO - 10.1080/21532974.2019.1588611 DP - DOI.org (Crossref) VL - 35 IS - 2 SP - 76 EP - 78 J2 - Journal of Digital Learning in Teacher Education LA - en SN - 2153-2974, 2332-7383 ST - Considering Contextual Knowledge UR - https://www.tandfonline.com/doi/full/10.1080/21532974.2019.1588611 Y2 - 2025/06/09/08:11:40 ER - TY - JOUR TI - The impact of ChatGPT on higher education AU - Dempere, Juan AU - Modugu, Kennedy AU - Hesham, Allam AU - Ramasamy, Lakshmana Kumar T2 - Frontiers in Education AB - Introduction This study explores the effects of Artificial Intelligence (AI) chatbots, with a particular focus on OpenAI’s ChatGPT, on Higher Education Institutions (HEIs). With the rapid advancement of AI, understanding its implications in the educational sector becomes paramount. Methods Utilizing databases like PubMed, IEEE Xplore, and Google Scholar, we systematically searched for literature on AI chatbots’ impact on HEIs. Our criteria prioritized peer-reviewed articles, prominent media outlets, and English publications, excluding tangential AI chatbot mentions. After selection, data extraction focused on authors, study design, and primary findings. The analysis combined descriptive and thematic approaches, emphasizing patterns and applications of AI chatbots in HEIs. Results The literature review revealed diverse perspectives on ChatGPT’s potential in education. Notable benefits include research support, automated grading, and enhanced human-computer interaction. However, concerns such as online testing security, plagiarism, and broader societal and economic impacts like job displacement, the digital literacy gap, and AI-induced anxiety were identified. The study also underscored the transformative architecture of ChatGPT and its versatile applications in the educational sector. Furthermore, potential advantages like streamlined enrollment, improved student services, teaching enhancements, research aid, and increased student retention were highlighted. Conversely, risks such as privacy breaches, misuse, bias, misinformation, decreased human interaction, and accessibility issues were identified. Discussion While AI’s global expansion is undeniable, there is a pressing need for balanced regulation in its application within HEIs. Faculty members are encouraged to utilize AI tools like ChatGPT proactively and ethically to mitigate risks, especially academic fraud. Despite the study’s limitations, including an incomplete representation of AI’s overall effect on education and the absence of concrete integration guidelines, it is evident that AI technologies like ChatGPT present both significant benefits and risks. The study advocates for a thoughtful and responsible integration of such technologies within HEIs. DA - 2023/09/08/ PY - 2023 DO - 10.3389/feduc.2023.1206936 DP - DOI.org (Crossref) VL - 8 SP - 1206936 J2 - Front. Educ. SN - 2504-284X UR - https://www.frontiersin.org/articles/10.3389/feduc.2023.1206936/full Y2 - 2025/07/06/08:00:14 L1 - files/5279/Dempere et al. - 2023 - The impact of ChatGPT on higher education.pdf ER - TY - JOUR TI - Interpreting Black-Box Models: A Review on Explainable Artificial Intelligence AU - Hassija, Vikas AU - Chamola, Vinay AU - Mahapatra, Atmesh AU - Singal, Abhinandan AU - Goel, Divyansh AU - Huang, Kaizhu AU - Scardapane, Simone AU - Spinelli, Indro AU - Mahmud, Mufti AU - Hussain, Amir T2 - Cognitive Computation AB - Abstract Recent years have seen a tremendous growth in Artificial Intelligence (AI)-based methodological development in a broad range of domains. In this rapidly evolving field, large number of methods are being reported using machine learning (ML) and Deep Learning (DL) models. Majority of these models are inherently complex and lacks explanations of the decision making process causing these models to be termed as 'Black-Box'. One of the major bottlenecks to adopt such models in mission-critical application domains, such as banking, e-commerce, healthcare, and public services and safety, is the difficulty in interpreting them. Due to the rapid proleferation of these AI models, explaining their learning and decision making process are getting harder which require transparency and easy predictability. Aiming to collate the current state-of-the-art in interpreting the black-box models, this study provides a comprehensive analysis of the explainable AI (XAI) models. To reduce false negative and false positive outcomes of these back-box models, finding flaws in them is still difficult and inefficient. In this paper, the development of XAI is reviewed meticulously through careful selection and analysis of the current state-of-the-art of XAI research. It also provides a comprehensive and in-depth evaluation of the XAI frameworks and their efficacy to serve as a starting point of XAI for applied and theoretical researchers. Towards the end, it highlights emerging and critical issues pertaining to XAI research to showcase major, model-specific trends for better explanation, enhanced transparency, and improved prediction accuracy. DA - 2024/01// PY - 2024 DO - 10.1007/s12559-023-10179-8 DP - DOI.org (Crossref) VL - 16 IS - 1 SP - 45 EP - 74 J2 - Cogn Comput LA - en SN - 1866-9956, 1866-9964 ST - Interpreting Black-Box Models UR - https://link.springer.com/10.1007/s12559-023-10179-8 Y2 - 2025/07/08/13:21:26 L1 - files/5281/Hassija et al. - 2024 - Interpreting Black-Box Models A Review on Explainable Artificial Intelligence.pdf ER - TY - JOUR TI - Acceptance of artificial intelligence among pre-service teachers: a multigroup analysis AU - Zhang, Chengming AU - Schießl, Jessica AU - Plößl, Lea AU - Hofmann, Florian AU - Gläser-Zikuda, Michaela T2 - International Journal of Educational Technology in Higher Education AB - Abstract Over the past few years, there has been a significant increase in the utilization of artificial intelligence (AI)-based educational applications in education. As pre-service teachers’ attitudes towards educational technology that utilizes AI have a potential impact on the learning outcomes of their future students, it is essential to know more about pre-service teachers’ acceptance of AI. The aims of this study are (1) to discover what factors determine pre-service teachers’ intentions to utilize AI-based educational applications and (2) to determine whether gender differences exist within determinants that affect those behavioral intentions. A sample of 452 pre-service teachers (325 female) participated in a survey at one German university. Based on a prominent technology acceptance model, structural equation modeling, measurement invariance, and multigroup analysis were carried out. The results demonstrated that eight out of nine hypotheses were supported; perceived ease of use ( β  = 0.297***) and perceived usefulness ( β  = 0.501***) were identified as primary factors predicting pre-service teachers’ intention to use AI. Furthermore, the latent mean differences results indicated that two constructs, AI anxiety (z = − 3.217**) and perceived enjoyment (z = 2.556*), were significantly different by gender. In addition, it is noteworthy that the paths from AI anxiety to perceived ease of use ( p  = 0.018*) and from perceived ease of use to perceived usefulness ( p  = 0.002**) are moderated by gender. This study confirms the determinants influencing the behavioral intention based on the Technology Acceptance Model 3 of German pre-service teachers to use AI-based applications in education. Furthermore, the results demonstrate how essential it is to address gender-specific aspects in teacher education because there is a high percentage of female pre-service teachers, in general. This study contributes to state of the art in AI-powered education and teacher education. DA - 2023/09/04/ PY - 2023 DO - 10.1186/s41239-023-00420-7 DP - DOI.org (Crossref) VL - 20 IS - 1 SP - 49 J2 - Int J Educ Technol High Educ LA - en SN - 2365-9440 ST - Acceptance of artificial intelligence among pre-service teachers UR - https://educationaltechnologyjournal.springeropen.com/articles/10.1186/s41239-023-00420-7 Y2 - 2025/07/10/06:19:13 L1 - files/5283/Zhang et al. - 2023 - Acceptance of artificial intelligence among pre-service teachers a multigroup analysis.pdf ER - TY - JOUR TI - A Systematic Review of Generative AI for Teaching and Learning Practice AU - Ogunleye, Bayode AU - Zakariyyah, Kudirat Ibilola AU - Ajao, Oluwaseun AU - Olayinka, Olakunle AU - Sharma, Hemlata T2 - Education Sciences AB - The use of generative artificial intelligence (GenAI) in academia is a subjective and hotly debated topic. Currently, there are no agreed guidelines towards the usage of GenAI systems in higher education (HE) and, thus, it is still unclear how to make effective use of the technology for teaching and learning practice. This paper provides an overview of the current state of research on GenAI for teaching and learning in HE. To this end, this study conducted a systematic review of relevant studies indexed by Scopus, using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The search criteria revealed a total of 625 research papers, of which 355 met the final inclusion criteria. The findings from the review showed the current state and the future trends in documents, citations, document sources/authors, keywords, and co-authorship. The research gaps identified suggest that while some authors have looked at understanding the detection of AI-generated text, it may be beneficial to understand how GenAI can be incorporated into supporting the educational curriculum for assessments, teaching, and learning delivery. Furthermore, there is a need for additional interdisciplinary, multidimensional studies in HE through collaboration. This will strengthen the awareness and understanding of students, tutors, and other stakeholders, which will be instrumental in formulating guidelines, frameworks, and policies for GenAI usage. DA - 2024/06/13/ PY - 2024 DO - 10.3390/educsci14060636 DP - DOI.org (Crossref) VL - 14 IS - 6 SP - 636 J2 - Education Sciences LA - en SN - 2227-7102 UR - https://www.mdpi.com/2227-7102/14/6/636 Y2 - 2025/07/10/06:27:07 L1 - files/5285/Ogunleye et al. - 2024 - A Systematic Review of Generative AI for Teaching and Learning Practice.pdf ER - TY - JOUR TI - Exploring pre-service teachers’ generative AI readiness and behavioral intentions: A pilot study AU - Bui, Phuong AU - Korhonen, Tiina AU - Kontkanen, Sini AU - Karme, Sorella AU - Piispa-Hakala, Satu AU - Veermans, Marjaana T2 - LUMAT: International Journal on Math, Science and Technology Education AB - Generative Artificial Intelligence (GenAI) has rapidly emerged as a field capable of creating unique content across various areas. While offering significant potential, it presents challenges including ethical concerns, content inaccuracies, and increased challenges for educators who must adapt to fast-evolving technologies. Integrating GenAI tools into teacher education represents an urgent global research priority. This pilot study explores GenAI readiness, experiences, perceptions, and behavioral intentions among Finnish pre-service teachers while examining the feasibility of the GenAI Readiness Scale as a measurement instrument. Using a mixed-methods approach combining quantitative survey data (N=77) with qualitative responses (n=56) from open-ended questions, the research provides a nuanced analysis of future educators’ positioning toward GenAI integration in educational settings. Findings reveal a significant adoption gap, with 27% of participants never used GenAI tools as of April-June 2024, while majority engaged sporadically. Despite low perceived accuracy, frequent users continued utilizing GenAI, suggesting that usability, efficiency, and creative support outweigh accuracy concerns. Ideation and content creation emerged as the most common GenAI-supported tasks, while self-regulated and adaptive learning remained underutilized, indicating limited awareness of GenAI’s broader potential. Challenges primarily involved output quality and prompting difficulties. Participants preferred modifying AI outputs rather than refining prompts, employing strategies like output modification and external verification, though critical evaluation wasn’t always explicit. These findings highlight the need for structured AI literacy training in teacher education, emphasizing prompt engineering, evaluative judgment, and strategic AI integration. This study underscores the importance of developing GenAI competencies among pre-service teachers to ensure effective, responsible, and pedagogically meaningful AI adoption. Future research should explore longitudinal adoption trends, and impact of AI literacy training on teaching and learning practices. DA - 2025/08/13/ PY - 2025 DO - 10.31129/LUMAT.13.1.2755 DP - DOI.org (Crossref) VL - 13 IS - 1 SP - 8 J2 - LUMAT SN - 2323-7112 ST - Exploring pre-service teachers’ generative AI readiness and behavioral intentions UR - https://journals.helsinki.fi/lumat/article/view/2755 Y2 - 2025/08/15/07:09:21 ER - TY - GEN TI - The Rapidly Evolving Landscape of ChatGPT in Mathematics Education: A Comprehensive Scoping Review (2023-2025) AU - Bui, Phuong AU - Pongsakdi, Nonmanut AU - McMullen, Jake AU - Veermans, Marjaana AB - The rapid rise of ChatGPT and other large language models (LLMs) has drawn significant attention to their potential impacts on research and educational practices, necessitating critical evaluation and adaptation. In mathematics education, questions remain about the affordances, challenges and opportunities associated with these Generative Artificial Intelligence (Gen AI) tools. This study presents a comprehensive scoping review of 28 studies to examine the current applications, methodologies, and impacts of ChatGPT in mathematics education. Our findings indicate that most research emphasizes tool-driven evaluations of ChatGPT’s performance in solving mathematical problems, with limited exploration of human-AI interactions and user perceptions. While studies span various educational levels, the majority addresses K-12 mathematics. ChatGPT shows strengths in solving procedural and straightforward problems, providing step-by-step explanations, and clarifying concepts especially in lower-complexity mathematics. However, its limitations in solving complex, multistep problems, or those that require visual and spatial reasoning, and its tendencies to hallucinate or produce verbose responses pose challenges, particularly for learners with limited mathematical proficiency. These findings underscore the need for future research on ChatGPT’s integration in specific educational contexts, with a focus on human-driven approaches and development of pedagogical practices. They also highlight the potential of ChatGPT and similar Gen AI tools in mathematics education when used thoughtfully and strategically. To realize this potential, teacher training and professional development should focus on equipping educators with technological knowledge and technical skills necessary to effectively incorporate Gen AI tools into their instructional practices. DA - 2025/08/24/ PY - 2025 DO - 10.31219/osf.io/ce2ky_v2 DP - DOI.org (Crossref) PB - Open Science Framework ST - Affordances, Challenges, and Opportunities of ChatGPT in Mathematics Education UR - https://osf.io/ce2ky_v2 Y2 - 2025/08/31/08:32:41 ER -