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Since ChatGPT exploded onto the scene in October 2022, the media has been breathless with their discussion about how it is going to impact many aspects of life and work. In order to bring this new reality of generative AI into the "Introduction to Management Information Systems" classroom at both the undergraduate and graduate levels, we have developed two short cases that can be completed in or out of the classroom. These cases allow students to use generative AI for an interesting and useful purpose and develop prompts to deliver the output. Students can begin to learn what generative AI can do for them, and how it can shape their future careers. We tested the perceived effectiveness of the project on students using a pre/post survey. The results are analyzed using a paired t-test and demonstrate that students increased their understanding of generative AI and prompt engineering.

This research was conducted to see if using ChatGPT prompts students to think more deeply through reflection reports. The case study method and qualitative research methodology were used to carry out this study. Five graduate students in the Curriculum and Instruction department at Aksaray University's Social Sciences Institute who were teachers in various subjects and employed at various state school levels participated in the study. It was found that the majority of participants accepted all of the information presented by ChatGPT based on a citation as true, did not feel the need to control data reliability, and could be manipulated by ChatGPT while doing self-evaluation. Additionally, despite the fact that they prepared reflective reports in which they compared their essays with ChatGPT and included questions that prompted them to think critically and reflectively, as well as the fact that they had taken a graduate-level course on the teaching of higher order thinking skills, it was acknowledged that they could not demonstrate the expected performance in using higher order thinking skills other than to a limited extent. The onus should be on educators to pioneer positive examples of how to utilize ChatGPT and provide direction on how to harness its potential, supported by critical thinking, rather than to avoid using it and identify it as a tool to be avoided.

Mathematics education is looking for innovative methods to foster problem-solving skills in students. This research develops a problem-solving assessment using GeoGebra Classroom, a versatile interactive mathematics software, to revolutionize mathematics formative assessment and improve students' problem-solving skills. This study adopted the analysis, design, development, implementation, and evaluation (ADDIE) instructional design model stages. The design stage created a comprehensive assessment blueprint, incorporating GeoGebra Classroom functions to create interactive problem-solving tasks. Data analysis used both quantitative and qualitative approaches. Qualitative data consisted of feedback and suggestions from assessment experts, mathematicians, and GeoGebra specialists. Meanwhile, quantitative data included expert scores and cognitive tests that measured students' problem-solving abilities. A cognitive post-test was conducted to measure the progress of students' understanding while using the assessment product. The results of the content validity analysis, assessed using Aiken's V, ranged from 0.85 to 0.92, indicating a high level of validity for the problem-solving skills assessment in terms of content and construction. Some revisions were made to the design of the developed media to make it more interactive for students. These findings suggest that we can further use problem-solving questions integrated with GeoGebra Classroom to uncover the problem-solving skills of junior high school students.

This study delves into the opportunities and challenges associated with the deployment of AI tools in the education sector. It systematically explores the potential benefits and risks inherent in utilizing these tools while specifically addressing the complexities of identifying and preventing academic dishonesty. Recognizing the ethical dimensions, the paper further outlines strategies that educational institutions can adopt to ensure the ethical and responsible use of AI tools. Emphasizing a proactive stance, the paper suggests that by implementing these strategies, schools can harness the benefits of AI tools while mitigating the risks associated with potential misuse. As the adoption of AI tools in education continues to expand, all stakeholders must stay abreast of the latest developments in the field. This knowledge equips educators to navigate the opportunities and challenges posed by AI tools, fostering a learning environment that is both secure and conducive to empowering students to realize their full potential.

The objectives of this research were to: 1) develop online lessons with the Google Classroom application on computer system operation for secondary 2 (Grade 8) students; 2) study pre-test and post-test academic achievement; and 3) study the students' satisfaction with the online lessons with the Google Classroom application on computer system operation for secondary 2 (Grade 8) students. The sample consisted of 20 students from secondary 2 (Grade 8) studying computational science at Sappasamit Bamrung Municipal School. They were selected for purposive sampling. The research instruments consisted of online lessons with the Google Classroom application, a quality evaluation guide towards media and content achievement tests, and evaluation forms of students' satisfaction. The data analysis statistics were the standard deviation and dependent sample t-tests. The research results indicated that: 1) the online lessons with the Google Classroom application on computer system operations had the quality of media at an excellent level with an average of 4.58, quality of contents with an average of 4.55, and efficiency criterion of 82/81. 2) The students had an average pre-test score of 17.40, while the satisfaction of students towards online lessons with Google Classroom application is at a high level." post-test was 24.35. The t-test analysis during and after learning was different at .05 statistically significant levels, and 3) students' satisfaction toward lessons with Google Classroom location at a high level of 4.49.

This research study focuses on the growing concern of academic misconduct in distance education courses. A quasi-experimental study was conducted to measure the impact of introducing webcam recording software as an online supervision tool for high-stakes exams in two separate online courses (Management and Accounting). Results revealed that overall performance decreased following implementation of the software, and persisted after taking potential confounding factors into account. Additionally, the explanatory power of the regression analysis was higher for scores under supervision, which suggests that cheating was occurring before online supervision was introduced. It can be concluded from this study that online supervision is an effective tool to combat academic dishonesty in distance education courses.

In an era of major advances in the digital world, artificial intelligence has been a part of programs, tools, applications, and platforms. It has also been integrated into fields of education including language teaching and learning. To this end, ChatGPT, one of the most recent AI-driven systems, has been proposed to support language learners' personalized studies. Thus, this paper presents a qualitative study aiming to explore how Turkish EFL learners in higher education use ChatGPT for speaking. For a deeper understanding, the study was designed as a case study which used multiple sources to collect qualitative data. In this sense, semi-structured interviews were held with the participants, and through open-ended questions, they were asked about their study habits and any background knowledge about ChatGPT. In a following session, they were introduced the chatbot and instructed on possible ways to use it for speaking practice. Screen recordings of the usage by the participants were another source to observe and later describe the process for the researcher. A final session of the interviews planned as a stimulated recall was held to explore the participants' ChatGPT use experience through their reflection. The thematic analysis of the data revealed codes and themes leading to language teaching implications about learner characteristics and use of AI for language studies.

The technology-supported education systems seamlessly integrated throughout the globe in response to the demands of post COVID-19 pandemic. The swift developments of the digital tools with Artificial Intelligence (AI) support are also readily diffused among the educational communities. This research paper investigates the synergistic impact of digital literacy, the incorporation of AI tools, and Peer Supported Collaborative Learning (PSCL) on the learning perceptions of university students. The research aims to discern the implications of these technological and social facets on students' attitudes towards AI assisted learning process. Structured questionnaire-based survey among the University students were done for this descriptive research. 409 responses collected were analysed with SPSS, Excel and Process Macro. It is found that the students' Digital Literacy, Use of AI tools and PSCL on AI assisted learning were positively correlated. The partial mediatory path through the PSCL and AI tool usage has a significant positive influence on students learning process. The insights gathered from this study can inform educators, policymakers, and institutions on optimizing the amalgamation of digital literacy, AI tools and PSCL to enhance the contemporary learning environment. As universities navigate the digital age, this research provides a nuanced understanding of the dynamics shaping students' perceptions, offering valuable insights into the multifaceted aspects of AI influencing the educational landscape.

The burgeoning role of Artificial Intelligence (AI) in education prompts crucial discussions regarding its implications for teaching and learning. This qualitative study probes the argumentative perspectives of 118 teacher candidates from Igdir University on the integration of AI into educational practices. Employing Toulmin's (1958) model, we analyzed their arguments, which encompass claims, evidence, warrants, backings, rebuttals, and conclusions, to ascertain their stance on AI's pedagogical integration. Utilizing four distinct AI chatbots--GPT-4, Gemini AI, Claude 3 Haiku, and Mistral AI--the research deciphers thematic undercurrents within these dimensions. Moreover, a novel methodological contribution is made through 'negative space exploration', focusing on the unmentioned themes to identify latent biases and assumptions in the argumentation. The study's dual analytical approach, combining AI-driven theme identification and negative space exploration, resulted in an enriched understanding of the content. Key findings suggest a nuanced perception among participants: while AI chatbots are acknowledged for enhancing educational efficiency and enabling personalized learning, concerns regarding diminished human interaction, potential erosion of critical thinking skills, and ethical use persist. The analyses also highlight the need for a balanced AI implementation that supports, not supplants, traditional educational methods. This research contributes to the ongoing debate on effective AI integration in education and calls for responsible pedagogical adoption of AI technologies.

Eye-tracking (ET) method provides a promising channel for educational researchers to connect learning outcomes to cognitive processes. The main principle of ET is that our gaze and our focus of attention are connected. Due to the advent of digital technologies, eye tracking studies are increasingly growing in different fields and in mathematics education. We assume that the provided task is one of the ways to analyse deeply cognitive processes, and we wonder how ET studies are dealing with the integration of digital technology in task-design in geometry. Starting from Strohmaier et al. (2020) we found three studies, one focused on geometric proofs and two based on construction of geometric objects. We highlight the contributions of integrating digital technology in learning and instruction, and in research in geometry.

We examined how Learning Analytics literature represents participants from diverse societies by comparing the studies published with samples from WEIRD (Western, Industrialized, Rich, Democratic) nations versus non-WEIRD nations. By analyzing the Learning Analytics studies published during 2015-2019 (N = 360), we found that most of the studies were on WEIRD samples, with at least 58 percent of the total studies on WEIRD samples. Through keyword analysis, we found that the studies on WEIRD samples' research topics focused on self-regulated learning and feedback received in learning environments. The studies on non-WEIRD samples focused on the collaborative and social nature of learning. Our investigation of the analysis tools used for the studies suggested the limitations of some software in analyzing languages in diverse countries. Our analysis of theoretical frameworks revealed that most studies on both WEIRD and non-WEIRD samples did not identify a theoretical framework. The studies on WEIRD and non-WEIRD samples convey the similarities of Learning Analytics and Educational Data Mining. We conclude by discussing the importance of integrating multifaceted elements of the participant samples, including cultural values, societal values, and geographic areas, and present recommendations on ways to promote inclusion and diversity in Learning Analytics research.

This article investigates technologies used for knowledge sharing among rice farmers in the Eastern Region of Ghana and suggests ways by which the use of technologies may be enhance rice farming. The research was underpinned by the pragmatic paradigm where a concurrent triangulation mixed method design was adopted. The data was drawn from 101 survey respondents and nine interview participants, consisting of rice farmers, farm managers and extension officers. The findings revealed elementary use of technologies, tools and systems for knowledge sharing among the rice farmers. The main social media platform used for knowledge sharing was WhatsApp. The platforms that were used the least were Twitter, Facebook, LinkedIn, Imo and Instagram. Findings have implications for integrating various tools, technologies and systems into knowledge sharing among rice farmers. There is a need to address the challenges in structural-level technological infrastructures, architecture and functionalities, in order to build the technological competence of rice farmers. Farmers' knowledge of technology is influenced by training, motivation, and personal experiences. Previous studies on use of technologies in knowledge sharing focused on organisation. This article examines technology within the context of rice farming.

This study investigated the effects of a reading assistant software on the fluency and accuracy of speech production among EFL university students, employing a one-group pretest-posttest design. The participants included 50 Thai undergraduate English majors in their first and second years. Data were analyzed using paired samples t-tests to measure L2 oral fluency, specifically pruned speech rate (PSR) and mean length of run (MLR). Accuracy rate was assessed by quantifying the proportion of error-free clauses within the participants' speeches from the pretest and posttest and calculating the average number of error-free clauses per T-unit. Results indicated significant improvements in speech fluency, evidenced by longer uninterrupted speech segments, fewer disfluencies like filled pauses and repairs, and increased overall fluency. Additionally, the post-test showed a higher percentage of error-free clauses compared to the pretest, reflecting a substantial enhancement in grammatical accuracy. This suggests that the intervention had a positive impact on the participants' ability to produce grammatically accurate and error-free clauses. These outcomes suggest that the reading assistant software effectively enhances both the fluency and grammatical accuracy of speech production in EFL learners, underscoring its potential benefits in language education contexts.

AI-generated paraphrasing tools, especially QuillBot and Paraphrasing Tool, play a crucial role in preventing plagiarism in academic writing. However, their effectiveness and proficiency have been questioned, particularly regarding the adequacy of their strategies. This qualitative study analyzed the paraphrasing strategies and proficiency levels of QuillBot and Paraphrase Tool. Using a purposive sampling technique, all 30 abstracts from one issue of the "Journal of Second Language Writing" were paraphrased using the two paraphrasing tools in their standard modes, and the results were analyzed using the frameworks of Keck (2014) and Nabhan et al. (2021). The results of the study indicated that both tools primarily used synonym substitution, with QuillBot favoring word-level changes and Paraphrase Tool emphasizing sentence restructuring. QuillBot tended to show minimal revision, followed by moderate revision, while Paraphrase Tool exhibited more moderate revision, followed by minimal and substantial revision. Paraphrase Tool exhibited broader paraphrasing capability than QuillBot, but both tools show some paraphrasing limitations. Overall, while these tools may enhance some writing, writers should thoroughly review the core concepts of the original texts and grammatical structures in specific contexts. For novice writers, paraphrasing practice in classrooms should be conducted under teachers' guidance. AIgenerated tools should be secondary.

This paper is focused on the development of a didactic proposal for English students in the Basque Country. Specifically for students in the 1st year of "Bachillerato" with Spanish and Basque as their L1 and English as their L2 which aims to improve their communication skills, especially oral abilities and pronunciation, through the use of didactic dubbing. This proposal is framed within a project-based learning (PBL), in which the final project is the creation of a vertical video dubbed in English. For this purpose, six sessions have been designed with different group activities that will culminate with the presentation of the video. This didactic unit revolves around social networks and seeks to meet the requirements of current regulations in terms of objectives, contents, competences and evaluation criteria. In addition, transversal elements such as the appropriate use of social networks, fears or interpersonal relationships are worked on. The use of videos in vertical format meets the increasing demand for creating content in this format that adapts to the new mobile devices.

Building on previous research, this qualitative exploratory study investigates the impact of ChatGPT on English language classes among Korean university students. The researcher uses pre- and post-training surveys, in-class observations, and interviews to explore 120 students' perceptions of their experiences over a 15-week semester. Results indicate largely positive attitudes, with students expressing optimism about ChatGPT's potential to enhance language skills. Classroom engagement was high, fostering collaboration and active participation. Post-training interviews revealed improved confidence, collaborative learning experiences, and a shift toward metacognitive awareness in learners and autonomous learning. Some technical and language challenges surfaced, as well as skepticism from a small number of learners. Long-term post-training surveys highlight sustained engagement and real-world applications. The findings provide insights for educators and policymakers considering the integration of AI tools in language education, emphasizing the importance of ongoing support and flexibility in implementation strategies.

Data analytics is a rapidly growing field that plays a crucial role in extracting valuable insights from large volumes of data. A data analytics practicum course provides students with hands-on experience in applying data analytics techniques and tools to real-world scenarios. This practicum is intended to serve as a bridge between the student's academic environment and the professional application of their skills in an employment and internship setting. This study examined the design of a data analytics practicum course. The main objectives included (1) the identification of topics and skills employers look for in new hires in data analytics-related internships and entry-level positions, (2) the development and implementation of a Data Analytics practicum course and (3) reflection on the first-time offering of the course and suggested improvements for the next iteration. As part of this study, industry and organization survey responses drove the design of the course and development of key student learning gains for five learning modules throughout the semester. Faculty within the departments of information technology (IT), mathematics, and statistics collaborated in the construction, development, and implementation of team-teaching instructional practices of the Data Analytics Practicum in Spring 2023. This study applies an interdisciplinary approach to data analytics practicum development and instruction.

The research sought to study potential efficiency in course design and execution using Constructive Alignment, and then classroom workflow grounded in eduScrum based on the Agile Project Framework of Scrum for graduate classes in managerial analytics. The research measured performance based on the Scrum concept of Velocity, defined as the rate of improvement in learning as measured by the number of Constructive Alignments' Learning Objectives achieved. The process of class design creates a list of activities for each class that lends itself to a standardized learning workflow. Scrum, as a project framework originated within software development in the early 2000s, but has now become a managerial method of choice for projects in a wide variety of industries and sectors. The final product to be delivered is broken into increments of value that can be created by the team in short work periods, also called Sprints. EduScrum mimics the same approach, using each class session to act as a sprint in which the students are assigned to self-managed teams of students and assigned a list of learning activities to achieve. The teacher/professor's role shifts to coach, moving from team to team and improving workflow, overcoming barriers, providing resources, and ensuring each class maximizes value creation. Scrum and eduScrum rely on a short reflective learning session at the end of the Sprint, called a Retrospective, in which students and professors assess how they can improve the velocity of learning. Assessments are embedded for individuals as part of Constructive Alignment, and are connected to the Teaching/Learning Activities.

The contents of calculus, known for their complexity, present significant challenges for students, particularly in mastering multiple integrals and effectively visualizing related concepts. The transition to distance learning prompted by the COVID-19 pandemic has further complicated the learning process in multiple integrals. In line with this and considering the potential of computer-supported collaborative learning (CSCL), in this research we explore the impact of teaching in a CSCL environment on student achievements, focusing on students from the computer science study program. Through data analysis using ANOVA and Bonferroni post-hoc tests, it was found that students exposed to collaborative learning in GeoGebra environment demonstrated higher levels of theoretical and practical knowledge compared to peers who acquired knowledge without using GeoGebra. Additionally, this group of students achieved results comparable to those of students who attended traditional in-person teaching, showing noticeable improvements in solving complex tasks. Our findings show the effectiveness of CSCL approach in context of distance learning and highlight potential of collaborative environments enhanced with technology in facilitating student understanding and achievements in calculus education.

There has been an increasing demand for healthcare analytics skills and competence by healthcare organizations. Although many universities have established programs and courses on healthcare analytics, most of these curricula have been designed for information systems (IS), information technology (IT), or analytics students. It is unclear how these curricula would fit the needs of healthcare professionals who have little IT knowledge and background yet also need analytics for their clinical or administrative job roles. This research reports on the design of an executive MBA course intended for an audience of healthcare professionals. The learning objectives, topic coverage, software tools, and assessment methods are presented along with students' perceptions of these aspects of the course. Several important lessons learned are shared and future directions are proposed, which can help other educators design similar healthcare analytics courses for professional audiences.

The background of this research is the need for teacher innovation in developing digital-based learning media in Indonesian language learning. The research method used is research and development (R&D) with the analysis, design, develop, implement, and evaluate (ADDIE) model, which consists of five research stages: analysis, planning, development, implementation, and evaluation. Data collection techniques are questionnaires, in-depth interviews, observations, and documentation that present the results regarding innovation, features, applications, and the impact of using the "benkangen" game in learning Indonesian in elementary school. The subjects of this study were 25 teachers from 25 elementary schools, and 66 students from 10 elementary schools in Magelang district and Magelang city. The results showed innovation in the development of game applications based on Magelang local wisdom with game features in the form of puzzles of Magelang culture and local wisdom, Indonesian language learning materials packaged in the form of questions accompanied by the number of points in each answer, and audio that reflects local wisdom in Central Java. The novelty of this research is the development of the "benkangen" game based on Magelang local wisdom, which still needs to be developed by teachers in Indonesia. Future research needs to explore the innovation of Indonesian language learning games through the latest software.

Artificial intelligence (AI) has recently been gaining ground, particularly since November 2022, with the introduction of generative tools based on natural language processing and neural network algorithms. These kinds of tools have great potential for creators and users of Open Educational Resources (OER) and the Open Movement itself but they also represent risks. The International Council for Open and Distance Education OER Advocacy Committee (OERAC) developed two workshops to present the role of AI in OER at two international conferences in the fall of 2023. The workshops presented the features, benefits, key challenges, and practical issues related to using AI technologies from professional, ethical, sustainable, and equitable perspectives, while also focusing on the five areas of the UNESCO OER Recommendation. Participants were dynamically engaged in discussions, and documented their ideas in formats that could be used as OER in themselves. The OERAC noted and categorized the results, and developed short summaries and drafts for further work. Finally, drawing on the findings from the workshops, we asked ChatPDF for a second opinion on further suggestions for AI in connection with OER, which in turn related to the five areas of the recommendation. We conclude that, while there is great potential for the use of AI in the context of the Open Movement, there is also a need for professional ethics, equity, and sustainable capacity building, access, inclusion, policy, models, and international collaboration.

Recent advancements in generative artificial intelligence (GAI) have sparked debates and research on its transformative potential in education. This study explored how a specific group of educators partner with GAI tools, particularly ChatGPT, to complement and enhance their teaching. Within an interpretative paradigm, the study used an exploratory case study design to investigate how 13 educators enrolled as students in a structured master's programme at an open distance learning university in South Africa use GAI tools in their teaching. Their posts on a discussion forum were used to collect data. Findings reveal that they actively employ GAI to streamline their teaching practices, specifically to personalized tutors, simplifying English texts and translations, assessments, lesson planning, and critical thinking tasks. The study also highlights the need to understand the limitations and boundaries of GAI, including concerns about accuracy, biases and reliability. Importantly, the absence of institutional guidelines on GAI raises questions about the necessity for clear guidelines and policies to ensure responsible and ethical integration in educational contexts. The paper concludes by emphasizing the transformative potential of GAI and the fact that it will increasingly act as a partner in teaching and influence modern teaching practices. Ultimately, GAI's foothold in education is undeniable, challenging educators and policymakers to navigate its implications while maximizing its potential to support effective teaching.

This study tried to design a WhatsApp bot to be implemented in English language vocabulary learning context in Oman. 150 Omani English as a Foreign Language (EFL) students from three different proficiency levels were selected based on random sampling. To measure the effectiveness of the treatment, pretests, posttests, and delayed posttests were conducted, respectively. The TAM 2 extended questionnaire was also used to understand learners' perceptions regarding the use of the WhatsApp bot in the learning process. The results of the study revealed that the WhatsApp bot, on all three levels, works nicely and practically. Although experimental groups, who used WhatsApp bot, at elementary and intermediate levels showed significant differences from the traditional face-to-face classes, pre-intermediate students showed no significant difference between the two mentioned terms. It was also understood that chatbots could be the best supplementary materials assisting teaching in delivering materials.

Today math teachers can best reach their students and show them how math surrounds us by using manipulatives, children's literature, and GeoGebra while teaching mathematics. These are some of the best pedagogical practices for teaching mathematics today. In our high-tech world, students need to be proficient in science, technology, engineering, and mathematics (STEM) fields. As endorsed by National Council of Teachers of Mathematics (2000) and stressed in common core state standards in mathematics, it is important that we teach with technology, address dispositions and math anxiety, and make the math that young people are learning pertinent and meaningful. Frequently, it may be best to start teaching young people geometry first as opposed to numbers, which are considered more abstract and difficult to learn. Geometry is one of the most tangible divisions of math and concentrating on this first can help students' whole view of mathematics and their insolences towards learning the subject. Nowadays teachers also need to be cognizant and checking for attitudes and dispositions toward learning mathematics, as math anxiety is an issue in today's classrooms. This paper will revisit the best pedagogical practices for teaching math, the review of the use of math manipulatives, children's books, and GeoGebra to help teachers create mathematically confident young people.

Learning must be able to develop knowledge, skills, and mindsets so that the graduates produced have attitudes, abilities and knowledge that are integrated and skilled in life. One way to achieve learning can be done through habits of mind because the success of learning is strongly influenced by habits of mind. The purpose of this study is to as certain how habits of mind and cognitive learning outcomes in biology are affected by learning process oriented guided inquiry learning with blended learning support. A pretest-postest design wih a non-equivalent control group was employed in this study. The trial ran from February to June 2022. Utilizing the habits of mind questionnaire, pupils' thought patterns were assessed. Essay tests are also used to evaluate the results of cognitive learning. In this study, google form, LMS, and google meet were used for data collection. Statistical Product and Service Solutions software version 23 is used for data analysis and the results of covariance analysis (ANCOVA) showed a p value < 0,005, meaning that POGIL-supported blended learning can empower habits of mind and cognitive learning outcomes in biology learning. There is a substantial difference between the outcomes of the least significant difference and increasing habits of mind and cognitive learning outcomes. As a result, POGIL with moodle support can be used to enhance students' habits of mind and cognitive learning results in biology classes.

Gamification can make learning more fun and engaging for students. Software engineering can utilize gamification to help students learn and improve their skills from the complexity of software engineering. This study used quantitative research to examines perceived ease of use, student satisfaction, and perceived usefulness to measure gamification quality, which can have an impact on software engineering intention, namely intention, loyalty, and participation in following and understanding software engineering materials. The data was collected based on an online questionnaire survey, 90 data were collected and then measured and analyzed using SmartPLS 3. The results showed that perceived ease of use, student satisfaction, and perceived usefulness have a significant influence on gamification quality, which also leads to a positive impact on software engineering intention. This research guides teachers and educational institutions that gamification is very successful as a learning medium to simplify complex information to be more interactive.

This review explores how artificial intelligence (AI henceforth) can reshape education through insights from situated learning literature. The objective was to critically examine opportunities and challenges of situated learning, and how AI could augment strengths while overcoming obstacles. A systematic review using the PRISMA method analyzed 60 articles from peer-reviewed journals over three decades. Key concepts associated with situated learning were extracted and analyzed qualitatively and quantitatively. Findings identified major obstacles: the traditional school system's one-way passive learning; the predominant educational approach fixated on predefined outcomes; and teachers' lack of contextual knowledge. AI presents solutions including adaptive systems tailored to students' evolving needs; intelligent tutoring situated in authentic scenarios; automation of administrative tasks; and data-driven teacher support. When implemented thoughtfully, AI has the potential to enhance situated learning through increased personalization, interactivity, and real-world connections. This promises a better effective, adaptive education - but human guidance remains essential for ethical grounding. This review offers teachers, researchers, and policymakers valuable insights on integrating both AI and situated learning to keep education relevant in an interconnected world.

The current study attempted to measure the impact of using an interactive WhatsApp bot designed using Python language programming in grammar learning. To this end, sixty Omani pre-intermediate English proficiency learners were the sample population of this study to act as a control and experimental group, with an equal number of students in each group. A pretest was conducted to measure students' grammatical knowledge and ensure the homogeneity of the students before treatment. Although both groups received in-class instructions on using grammar, the experimental group received treatment that used an interactive WhatsApp bot as an extra facilitator to obtain materials outside of the classroom. After the treatment period, a posttest was conducted to compare the results of the two groups. Three weeks later, a delayed post-test was conducted to check the students' retention of the grammatical structure. The study's findings showed that both groups progressed in the posttest, which could result from teachers` instructions; however, the experimental group showed statistically significant progress in the posttest compared to the control group. The results of this study could provide better opportunities for teachers, students, and institutions to work efficiently and accurately in an academic environment.

This research used qualitative netnography to examine the use of Duolingo German discussion boards among users of varying levels of engagement. The sample contained six participants of various levels of engagement. The criteria for selecting participants were based on usage counts in the discussion board community. This study aimed to examine information that could answer the research question, "How do individual Duolingo German users use discussion boards over time among highly engaged, moderately engaged, and lower engaged users?" The netnographic analysis resulted in three themes: (1) highly engaged users continue to contribute to discussions over time; (2) moderately engaged users seek educational supplementation in their conversations; and (3) lower engaged users are more likely to participate in the discussion boards to connect socially about tangential topics over the span of months. The analysis indicated that the frequency of engagement is related to the content of the comments posted. In understanding how users engage with the discussion boards over time and the frequency of engagement, researchers and educators may be more informed about how users utilize the discussion boards to tutor, learn, and socialize.

This research investigates the comparative effectiveness of the ChatGPT and the Google search engine in facilitating the self-learning of JavaScript functions among undergraduate open and distance learning students. The study employed a quasi-experimental post-test control group design to analyze the variables of disorientation, satisfaction, cognitive load, navigation performance, and test scores among 471 learners. Results indicated a marked advantage for ChatGPT users in reducing cognitive load and disorientation, improving navigation performance and increasing test scores. The study also explores the evolving dynamics between conventional keyword-based search engines and AI-driven conversational models, reflecting on their mutual influence in the domain of information retrieval. These findings suggest that AI chatbots like ChatGPT not only enhance the learning experience but also signify a paradigm shift in how information is accessed and processed in educational settings. The research contributes to understanding AI applications in education, particularly in self-directed learning scenarios in open and distance learning.

This study investigates how Saudi Arabian special education teachers believe about online learning for students with disabilities evaluating their familiarity with the subject and identifying factors affecting their preparedness to adopt this mode of instruction. Researchers aim to understand educators' perceptions of delivering special education through online platforms in Saudi Arabia through a cross-sectional analysis of quantitative data complemented by responses to three open-ended questions. The study involves 130 in-service special education teachers currently employing online methods to teach students with disabilities. The research findings reveal key insights: Firstly, most participants (79%) viewed online learning as beneficial for their students, echoing prior research highlighting its feasibility for students with disabilities. Secondly, many teachers indicated gaps in their knowledge (34%) and confidence (31%) related to online instruction emphasizing the need for tailored professional development. Lastly, challenges related to internet access (36%) and software availability (35%) underline infrastructure barriers requiring attention to facilitate effective online education for individuals with disabilities in Saudi Arabia. These findings underscore the importance of ongoing professional development and infrastructure enhancements to optimize the online learning experience in Saudi Arabia. This paper concludes by outlining practical implications and suggesting avenues for future research.

This article reports the results of an explorative, quantitative study designed to investigate the pedagogical potential of Flip (formerly Flipgrid) as a connectivist and transmedia tool for developing English language learners' productive skills to provide a basis for their continued improvement. The study suggests that the connectivist practice via Flip provides significant effect on improving secondary school students' productive skills. A total of 39 students, divided randomly into one experimental group and one control group, participated in the study during the eight-week curriculum involving an English course. Participants in the experimental group (n = 19) used Flip as a learning tool, whereas the control group participants (n = 20) followed the same curriculum without Flip. Pre- and posttests were used to compare the participants' speaking and writing productions before and after the project. These tests were evaluated based on a comparison of their mean scores by SPSS (Statistical Package for the Social Sciences) software. We used Questionnaires to analyze the positive and negative aspects of Flip. An independent samples t-test revealed that the experimental group outperformed the control group and showed the potential of regular Flip narrative-based tasks for developing English language learners' productive skills (p [less than or equal to] 0.05 = 0.039). Thus, Flip can be used by teachers and learners to improve speaking and writing, and thus overcome the limitations on time, practice, and feedback inherent in classroom-based courses.

This research examines the application of students' computational thinking (CT) in solving numerical method problems through computer software. Data collection involved observing their learning process and conducting tests to evaluate their CT skills within the context of the root approach material using Newton-Raphson method. The results indicate that the use of Microsoft Excel facilitates problem-solving for students and educators when employing Newton-Raphson method. Furthermore, it helps identify aspects or indicators of CT in students' problem-solving processes. The research findings demonstrate that students with strong mathematical abilities should document their conclusions in the algorithmic aspect. Students with moderate mathematical abilities exhibit all indicators in every aspect of CT when solving problems using Newton-Raphson method. On the other hand, students with weak mathematical skills fail to articulate questions, formulas, or conclusions in the algorithm design aspect, but they do show all indicators in the pattern recognition and abstraction aspects.

Calculating analytical uncertainties as a part of method validation is a relevant aspect of field and laboratory practices in instrumental analytical chemistry subjects, which usually require complex algorithms. This work describes the development and didactic use of an automatic and straightforward informatics tool, implemented in an Excel macro, for calculating and interpreting the uncertainty of an analytical method against a reference method on field measurements. The software was initially developed for field testing of low-cost air quality monitoring analytical methods against reference methods, and the present work shows its adaptation to a didactic environment. The uncertainty calculation software was implemented through an Excel macro based on Visual Basic as a graphical user interface. It finds a best-fit line that describes the relation between concentrations determined by the candidate and reference methods. The software generates the analytical validation results (slope and intercept with their respective confidence limits, and expanded uncertainty of a concentration determined by the candidate method), hiding the intermediate functions and calculations. The Excel interface eases uncertainty calculations for undergraduate students, although the background mathematics can be quickly unveiled to students for didactic purposes. This tool has been applied to a laboratory exercise focused on validating experimental results obtained in the measurement of ozone levels in ambient air by passive sampling and spectrophotometric detection. The uncertainty calculation software has proved valuable by providing the student a resource to check the analytical quality of the data generated in the laboratory, while assimilating the fundamentals behind the calculations.

This paper is part 4 in a series of workshops that examine the properties of some simple models of vocabulary networks. This Workshop explores how the overall activity level of a vocabulary network can be altered by changing the connections in the network (i.e., by implementing relinking events). The Workshop is linked to an online practice room where readers can explore these processes for themselves.

The Chat Generative Pretrained Transformer (ChatGPT) is a state-of-the-art artificial intelligence (AI) language model developed by OpenAI. It employs advanced deep-learning algorithms to generate text that mimics human language. ChatGPT, launched on November 30, 2022, has rapidly gained widespread recognition. Its influence on the future of technology and artificial intelligence is anticipated to grow even more, considering it has achieved such significance in less than two years since its release. This study investigated the potential of ChatGPT as a tool for enhancing the learning of Maltese for adult international students. This study involved 41 participants who embarked on a journey of exploration and employed ChatGPT for two weeks to support their Maltese learning. The study evaluated the effectiveness of ChatGPT through surveys and focus group discussions and revealed that while ChatGPT was convenient and accessible, its ability to provide accurate responses to students' questions and support Maltese grammar, vocabulary, and conversational practice was limited. The participants expressed frustration with the ChatGPT's limitations in understanding and responding to the Maltese language. This study emphasizes the need to fully unleash the potential of ChatGPT by improving its training on the Maltese language and collaborating with Maltese language and AI experts to better support Maltese language learning. These findings have important implications for the development of ChatGPT for less widely spoken languages such as Maltese.

Artificial intelligence becomes increasingly prominent in digital language teaching and learning and it will gain even more significance in the future of EFL education (cf. Schmidt & Strasser 2022). Therefore, it is key to explore how those who will shape this future perceive the newest development: pre-service EFL teachers. As Zheng puts it: "EFL pre-service teacher beliefs are the focus of change in the process of education" (2009), consequently their perceptions and beliefs regarding this evolving area of teaching and learning are of utmost importance. Focussing on the latest developments in ChatGPT, this paper aims to give a first insight into the potential and limitations of this AI platform from the perspectives of pre-service teachers in Germany. Therefore, this research project explores the following research questions: (1) Do student teachers consider ChatGPT relevant for their future teaching practice? (2) In which areas of language education do they see potential changes due to ChatGPT? In what ways? and (3) Are there any differences in the perception of ChatGPT between tech-savvy and non-tech-savvy student teachers? The research instrument is a combination of the "technology commitment" scale (Neyer et al. 2016) and items developed specifically for this research project. For RQ3, the analysis refers to existing preliminary work that was able to establish a relationship between technology commitment and the probability of technology application (cf. Knetzek & Christensen 2016). Based on the results of the survey, this paper then aims to offer new perspectives for EFL teacher education and outline concrete reflection activities that further pre-service teachers' critical engagement with AI in language education.

Concurrency is a complex to learn topic that is becoming more and more relevant, such that many undergraduate Computer Science curricula are introducing it in introductory programming courses. This paper investigates the combined use of Sonic Pi and Team-Based Learning to mitigate the difficulties in early exposure to concurrency. Sonic Pi, a domain-specific music language, provides great support for "playing" with concurrency, and "hearing" common problems such as data races and lack of synchronization among different concurrent threads. More specifically, the paper focuses on students' misconceptions regarding concurrency in Sonic Pi and compares them to those arising in traditional concurrent programming languages. In addition, it preliminarily explores knowledge transfer from Sonic Pi to C/C++. The approach has been applied in two teaching experiments with undergraduate students in our University involving 184 participants. Our investigations bring out the need to address misconceptions through targeted interventions for a clear understanding of concurrent programming concepts. Sonic Pi's simplified abstraction and domain-specific flavor has demonstrated to be effective, especially for first-year students.

This study aims to explain the relationships between secondary school students' digital literacy, computer programming self-efficacy and computational thinking self-efficacy. The study group consists of 204 secondary school students. A relational survey model was used in the research method and three different data collection tools were used to collect data. The structural equation model was used in data analysis to reveal a model that explains and predicts the relationships between variables. According to the results of the research, it was determined that digital literacy of secondary school students affected their computer programming self-efficacy, digital literacy affected their computational thinking self-efficacy, and computer programming self-efficacy affected their computational thinking self-efficacy. It was also found that digital literacy skills have an indirect effect on secondary students' computational thinking self-efficacy on computational thinking self-efficacy.

The paper discusses an alternative method of assessing the difficulty of pupils' programming tasks to determine their age appropriateness. Building a program takes the form of its successive iterations. Thus, it is possible to monitor the number of times such a program was built by the solver. The variance of the number of program builds can be considered as a criterion of the difficulty of the task. We seek to verify whether this variance is the greatest in the age group for which the task is most suitable. We created several series of programming tasks and offered them to 87000 pupils from 4th to 13th grade. For each task, we compared the optimal age group determined by the variance of the number of program builds method with the group determined by the correct answer ratio method. A strong correlation was observed in traditional microworlds Karel the Robot and Turtle. A moderate correlation was achieved in the new microworld Movie.

Effect sizes are important because they are an accessible way to indicate the practical importance of observed associations or differences. Standardized mean difference (SMD) effect sizes, such as Cohen's d, are widely used in education and the social sciences -- in part because they are relatively easy to calculate. However, SMD effect sizes assume normally distributed data, whereas most data in these fields are ordinal and/or non-normal. In these situations, SMD effect sizes can be biased, and a non-parametric measure such as Cliff's [delta] is more appropriate. This paper provides a practical guide on how to calculate Cliff's [delta]. First, we present a conceptual overview and a worked example. Then we present two methods of calculating Cliff's [delta]: (1) a web-based Shiny application developed to accompany this paper (https://cliffdelta.shinyapps.io/calculator; suitable for all users), and (2) an R tutorial (suitable for R users). This is intended to provide researchers and practitioners with an appropriate and accessible effect size measure for non-normal data.

This research paper explores the integration of ChatGPT as a tool for interactive learning of numerical methods in a differential equations (DEs) course. DE course is crucial for engineering students to model real-world phenomena. However, many DE courses focus only on analytical solutions and neglect important numerical solutions. To overcome this gap, an active learning approach was adopted, where students were asked to select a real-life phenomenon in their field of interest, find an appropriate model to describe it using DEs, and subsequently solve DE numerically using various numerical methods. The authors allowed students to use ChatGPT to generate codes and learn how to adapt them to their personalized learning needs. The findings derived from the students' survey responses demonstrated that ChatGPT significantly enhanced their interests and improved their coding skills. Students reported increased engagement and excitement in their learning journey with the integration of ChatGPT. By sharing this experience, we aim to inspire other educators to explore the potential of innovative technologies and instructional methods to enhance their own courses.

The procedures of carrying out factorial invariance to validate a construct were well developed to ensure the reliability of the construct that can be used across groups for comparison and analysis, yet mainly restricted to the frequentist approach. This motivates an update to incorporate the growing Bayesian approach for carrying out the Bayesian factorial invariance, as well as the frequentist approach, using the recent add-on R packages to show the procedures systematically for testing measurement equivalence via multigroup confirmatory factor analysis. The practical procedure and guidelines for carrying out factorial invariance under MCFA using a classic empirical example are demonstrated. Comparison between the frequentist and the Bayesian procedures and demonstration using priors are another two nuclei of the paper.

The low knowledge and love of students for culture, plus based on preliminary analysis, it is known that geometry skills are relatively low. The a need for harmony between student and teacher learning styles to maximize student engagement and focus in the classroom. So this study aims to create a culture-based Geometry learning design that effectively improves students' geometry skills in terms of students' learning styles and domicile. Furthermore, specifically examines geometry skills in terms of learning styles and student domicile. The subjects of the study were students of SMP Negeri 1 Ciruas and SMP Negeri 1 Tanara, Serang Regency. The research used the R&D method of prototype development model and quality research method. The results of the study found that the invention-based Ethnobra (Ethnomathematical Geogebra) design was valid, practical, and effective in improving students' geometry skills. The results of the subsequent analysis found that urban students had better geometry skills than rural students. It's also known that students with a tendency towards kinesthetic learning styles have the highest geometry skills. This study recommends that teachers use the Ethnobra model by integrating Geogebra applications in Geometry learning, especially for students who go to urban schools and with kinesthetic learning styles.