Learning Aids Research Articles

AI-Driven Transformations in Higher Education: A Citation and Co-citation Analysis

Integrating artificial intelligence (AI) in the educational field can revolutionize teaching and learning outcomes, increase research capacity, and expedite administrative processes. The application of AI-powered virtual learning aids, customized learning platforms, and intelligent educational platforms, can boost the engagement of students, offer real-time feedback and support, and aid customized learning. Additionally, AI-based administrative systems may automate repetitive processes like financial aid processing, enrolment, and admissions, freeing up important resources for more strategic endeavors. Thus, this study aims to synthesize the literature exploring AI’s impact on higher education through citation and co-citation analysis. Data from the Scopus database from 2015 to 2024 yielded 1140 papers. The data was analyzed using Biblioshiny and Vosviwer software to determine the publishing pattern, the most cited papers, the most prolific writers, sources, nations, and the network of co-citations between authors and references. The findings reveal a sharp and rapid growth (79.24%) in this industry, suggesting a significant spike in interest. In terms of overall citations, the UK became one of the top countries (1689). The author "Tan S" obtained the most citations (1869) with 10 publications, whereas "Kerr S" and "Poenici Sad" produced just one article and had the highest average citation (588). "Research And Practice in Technology-Enhanced Learning" and "Journal of Applied Learning and Teaching" were the most influential journals in terms of average and total citations, respectively. The uniqueness of the study is that it assesses the literature on AI's impacts in the fields of business and management as well as social science using citation and co-citation analysis. The outcomes of the study will have substantial implications that can help professionals, researchers, and decision-makers create policies.

Visual Aids in English Vocabulary Learning: an Intervention Proposal Among A2 Students’ Level in a High School in Loja City

Visual Aids in English Vocabulary Learning: an Intervention Proposal Among A2 Students’ Level in a High School in Loja City

Study on predicting new onset heart failure events in patients with hypertrophic cardiomyopathy using machine learning algorithms based on clinical and magnetic resonance features

Objective: To explore the value of predicting new-onset heart failure events in patients with hypertrophic cardiomyopathy (HCM) using clinical and cardiac magnetic resonance (CMR) features based on machine learning algorithms. Methods: The study was a retrospective cohort study. Patients with a confirmed diagnosis of HCM who underwent CMR examinations at Beijing Anzhen Hospital from May 2017 to March 2021 were selected and randomly divided into the training set and the validation set in a ratio of 7∶3. Clinical data and CMR parameters (including conventional parameters and radiomics features) were collected. The endpoint events were heart failure hospitalization and heart failure death, with follow-up ending in January 2023. Features with high stability and P value<0.05 in univariate Cox regression analysis were selected. Subsequently, three machine learning algorithms-random forest, decision tree, and XGBoost-were used to build heart failure event prediction models in the training set. The model performance was then evaluated using the independent validation set, with the performance assessed based on the concordance index. Results: A total of 462 patients were included, with a median age of 51 (39, 62) years, of whom 332 (71.9%) were male. There were 323 patients in the training set and 139 in the validation set. The median follow-up time was 42 (28, 52) months. A total of 44 patients (9.5% (44/462)) experienced endpoint events (8 cases of heart failure death and 36 cases of heart failure hospitalization), with 31 events in the training set and 13 in the validation set. Univariate Cox regression analysis identified 39 radiomic features, 4 conventional CMR parameters (left ventricular end-diastolic volume index, left ventricular end-systolic volume index, left ventricular ejection fraction, and late gadolinium enhancement ratio), and 1 clinical feature (history of non-sustained ventricular tachycardia) that could be included in the machine learning model. In the prediction models built with the training set, the concordance indices for the random forest, decision tree, and XGBoost models were 0.966 (95%CI 0.813-0.995), 0.956 (95%CI 0.796-0.992), and 0.973 (95%CI 0.823-0.996), respectively. In the validation set, the concordance indices for the random forest, decision tree, and XGBoost models were 0.854 (95%CI 0.557-0.964), 0.706 (95%CI 0.399-0.896), and 0.703 (95%CI 0.408-0.890), respectively. Conclusion: Integrating clinical and CMR features of HCM patients through machine learning aids in predicting heart failure events, with the random forest model showing superior performance.

Got alt hui. Some considerations on the German dialogue between Massimiliano Sforza and Maximilian I in the Liber Iesus (Milan, Archivio Storico Civico e Biblioteca Trivulziana, Cod. Triv. 2163)☆

AbstractThe so‐called Liber Iesus, a Latin prayer book commissioned for the young Massimiliano Sforza by his father Ludovico il Moro in the 1490s, features a splendid miniature depicting a meeting between the child count and Emperor Maximilian I. It is accompanied by a brief dialogue in German with an interlinear version in Italian on the topic of the Milanese‐Imperial alliance on the opposite page. Although the presence of a German version has often been discussed in research, no linguistic analysis has been conducted; statements about the dialogue's contents have apparently always been based on the Italian version. However, it has gone unnoticed that the German text shows a number of idiosyncratic forms that greatly limit its comprehensibility. This finding raises doubts about the common interpretation of the dialogue as a transcript or learning aid for a factual meeting between the two protagonists. In this paper, the language of the dialogue is analysed and the possible genesis of the text in its written form is reconstructed. Moreover, the potential functions of the dialogue beyond the communicative value of the language are discussed.

Canadian Muslim Excellence: A Time to Celebrate, Educate, and Reflect

This study redresses the limited presence of stories of Muslims in Canadian archival history and curriculum, drawing attention to the racial issues as an antidote, so that public awareness of anti-Islamophobia strategy can be made known. The authors searched, preserved, and distributed the diverse and inclusive stories of Muslim Canadians by employing a comprehensive, multidisciplinary strategy to map the political, ideological, institutional, and economic contributions of Canadian Muslims who are working for a better Canada. The authors made these stories readily available and accessible as an open educational resource under a Creative Commons’ license, by creating and constructing a digital archive. This research also works towards developing resources and connections for a range of audiences to develop learning aids to teach Muslim Canadians history. The fabric of this country would not be the same, if it were not for diversity. Muslim Canadians are valued contributors to the Canadian climate, and deserve to be celebrated, rather than mistreated. Sharing the stories of Muslim Canadians who have had a positive impact on this country is intended to increase the positive messaging surrounding some of the wonderful contributions Muslim Canadians have accomplished.

The Development of Machine Learning Models for Radial Compressor Monitoring With Instability Detection

Abstract Modern radial compressors are designed to operate with high performance and a wide range of applications while minimizing their environmental impact. It is necessary to study the machine near the stability limit and gain a comprehensive understanding of the fluid dynamic mechanisms that trigger the instability in the system to extend the operating range at high efficiency. Machine learning aids in developing pattern identification models for detecting compressor instability. In a prior study, a two-stage radial compressor for refrigerant gas underwent extensive simulation, capturing unsteady RANS conditions and generating a substantial dataset of pressure signals from multiple probes. Selected signals, coupled with detailed computational fluid dynamics (CFD) post-processing, revealed fluid dynamic structures near surge conditions. This study utilizes all pressure signals to assess the stage's operational state (stable, transient, or unstable/surge). An additional goal is to develop an algorithm predicting flow patterns in different stage sections with minimal pressure signals at the rotor inlet. This is a preliminary step toward the development of a smart monitoring and diagnostic model for the compressor installed in a plant. The developed model consists of three submodels, trained with CFD results obtained from unsteady Reynolds averaged Navier–Stokes (URANS) simulations. The three submodels are a regression submodule, a classification submodule, and a forecasting algorithm. The regression submodule predicts diffuser static pressure fields, the classification submodule categorizes whether the compressor is in a critical condition or not, and the forecasting algorithm predicts the inducer pressure signals in the future impeller rotations according to the actual operation history. These sub-modules work together to forecast whether the compressor, according to the operation strategy, is going into instability conditions.

INVESTIGATING THE IMPACT OF WEB-BASED LANGUAGE LEARNING (WBLL) THROUGH WRITE &amp; IMPROVE ON WRITING SKILLS IN SECONDARY SCHOOL

This study examines the impact of Web-Based Language Learning (WBLL) using the program Write &amp; Improve on secondary school students' writing skills at SM St. Michael, Penampang, using the Social Cognitive Theory (SCT). The study sought to investigate students' perspectives and impact in writing through guided practice and feedback. The technique used a two-cycle action research design that included both writing activities and open-ended surveys to collect information about students' writing performance and perceptions. Initial studies revealed that students struggled with the tool's UI and feedback mechanisms, restricting their development throughout the first cycle. However, significant increases were seen in the second cycle, with students obtaining higher CEFR bands and showing a greater grasp of feedback. Surveys revealed high satisfaction and perceived effectiveness of Write &amp; Improve, despite some technical issues and occasional inaccuracies in feedback. The study emphasizes the significance of teacher participation, as SCT and Vygotsky's Zone of Proximal Development (ZPD) indicate that directed learning and feedback can improve student outcomes. Researchers should conduct longitudinal investigations and perform different demographic testing. For educators, the findings emphasize optimal practices for incorporating WBLL technologies into instruction. This study adds to the growing body of knowledge about digital learning aids as well as providing ideas for better writing teaching through technology.

Time Efficient &amp; Cost Effective Online teaching tool with iConcepts in Orthodontics for DDS students @ UoM

Background Traditional teaching methods in Orthodontics include plaster models and photos which have been used for decades, however due to the nature of being static still images its difficult for 3-Dimensional (3D) changes in Orthodontics teaching, which has posed immense challenges as the learner is unable to clear concepts on the different planes that affect the final tooth positions not to mention the protracted treatment time ranges from 12 months (simple cases) to 36 months (complex cases). In 2024 with variety of platforms such as videos, 3D animations, interactive changes in face and teeth can be added to teaching tools for Orthodontics. Furthermore, orthodontic movements can pose difficulty in understanding the changes particularly in growing children adding to the 4th dimension. At UQ (Naser-ud-Din, 2015) and internationally (Bridges, 2015) provided experience with creating online teaching modules highlighting its strengths of flexibility, ease of access on demand and global presence. UQ developed SBLi -Scenario Based Learning interactive for Postgraduate Orthodontic students who found it highly engaging, with self-reflective and self-assessment elements useful. (Khoo et al., 2023; Naser-ud-Din, 2016). Generally simulations can be expensive to create (Kröger et al., 2017) and it’s essential to explore cost effective simulation teaching tools with industry partners for authentic learning experience. Aims There is a gap in the dental education sector, particularly with emerging CADCAM (Computer Assisted Design and Computer Assisted Manufacture), which can be used to enhance the learning of core concepts in biomechanics with the aid of 3D simulated online learning. This is reflected particularly for the university students in undergraduate courses who need to feel confident and clinically ready on graduation as Dentists. Thus, greater expectations to be aligned with current technological processes in dentistry. Over the past 5 years, in particular, there has been exponential improvements by the industry providing 3D simulations for treatment planning and patient communication, commonly referred to as the GPS for smile transformations. The aim of this presentation is to highlight the time efficiency and cost effectiveness of the learning tool in sync with contemporary demands in Orthodontics to provide authentic learning platform that prepares the clinician for real patients. Material &amp; Methods Currently the CAD CAM technology provide 3D simulations as open access to general public and doctors portal which can be utilized for teaching core concepts related to biomechanics foundations for student learning, engagement and self-assessment. This project envisages to create a novel forum encompassing education revolution as massive changes in delivery will occur with speed and efficiency internationally with onlinelearning demands. Hence, robust online presence with an interactive textbook such as iConcepts in Orthodontics under the banner of UoM to assist students in Doctor of Dental Surgery at MDS shall pave the way to learning needs for the future. Results The purpose of iConcepts a digital interactive online textbook is to create lifelong learning opportunities in safe space for visual, auditory and kinesthetic with quizzes for interactive learning of concepts without pressure in class learning and feeling judged by peers. Interactive 3D Orthodontic learning directly translates into clinical applications for various orthodontic cases. In the past decade CAD CAM has become clinically relevant particularly with Clear Aligner Therapy adding to higher precision and patient satisfaction. Moreover, it is imperative to have Long Term Retention (LTR) (Irvine, 2020) of learning new tasks. It is essential that students in dentistry are aware of the digital workflows and have clinical preparedness on graduation as it’s the future and certainly here to stay. Both qualitative and quantitative data on student experience shall be collected and analysed to seek out the best practices and processes for instruction of delivery in Orthodontics for DDS cohort in particular and lifelong learning for all ages in general encompassing time efficiency and cost effectiveness. Conclusion The current iConcepts is developed by the author with Apple Education and prototype is being assessed with MSc Data Science cohort at UoM. Furthermore, it is refined by Master of Science Software Engineering students at UoM. Future Recommendations Novel teaching tools shall be marketed to developing universities internationally assisting the dissemination of information a flagship for UoM and revenue generation for department of Education at UoM. In future there will be more and more demand towards interactive concepts clarification (Poblete et al., 2020) and self-assessments hence iConcepts provides that ideal platform. Such technologies will become more prevalent in the future particularly with AI and translated into different languages/ sectors of education. Various faculties that showcase start to finish particularly lengthy/complex outcomes can benefit with timelapse videos and 3D CADCAM for clarity and comprehension for the entire process such as patient journey throughout treatment in Orthodontics.

The Use of Machine Learning in the Diagnosis of Kidney Allograft Rejection: Current Knowledge and Applications.

Kidney allograft rejection is one of the main limitations to long-term kidney transplant survival. The diagnostic gold standard for detecting rejection is a kidney biopsy, an invasive procedure that can often give imprecise results due to complex diagnostic criteria and high interobserver variability. In recent years, several additional diagnostic approaches to rejection have been investigated, some of them with the aid of machine learning (ML). In this review, we addressed studies that investigated the detection of kidney allograft rejection over the last decade using various ML algorithms. Various ML techniques were used in three main categories: (a) histopathologic assessment of kidney tissue with the aim to improve the diagnostic accuracy of a kidney biopsy, (b) assessment of gene expression in rejected kidney tissue or peripheral blood and the development of diagnostic classifiers based on these data, (c) radiologic assessment of kidney tissue using diffusion-weighted magnetic resonance imaging and the construction of a computer-aided diagnostic system. In histopathology, ML algorithms could serve as a support to the pathologist to avoid misclassifications and overcome interobserver variability. Diagnostic platforms based on biopsy-based transcripts serve as a supplement to a kidney biopsy, especially in cases where histopathologic diagnosis is inconclusive. ML models based on radiologic evaluation or gene signature in peripheral blood may be useful in cases where kidney biopsy is contraindicated in addition to other non-invasive biomarkers. The implementation of ML-based diagnostic methods is usually slow and undertaken with caution considering ethical and legal issues. In summary, the approach to the diagnosis of rejection should be individualized and based on all available diagnostic tools (including ML-based), leaving the responsibility for over- and under-treatment in the hands of the clinician.

A Study on the Effectiveness of English Debate Competitions as a Language Learning Aid

English debate competitions have gained widespread attention as an innovative language learning tool in recent years. This study explores the impact of English debate on learners’ listening, speaking, reading, and writing skills, as well as their critical thinking and teamwork abilities. Using empirical research methods such as surveys, interviews, and performance evaluations, this study finds that participation in English debates not only improves students’ English proficiency but also significantly enhances their ability to think critically and collaborate effectively. By integrating recent literature, the research further examines the actual impact of English debate competitions on language learning and their application in educational contexts.

RadicalPy: A Tool for Spin Dynamics Simulations.

Radical pairs (electron-hole pairs, polaron pairs) are transient reaction intermediates that are found and exploited in all areas of science, from the hard realm of physics in the form of organic semiconductors, spintronics, quantum computing, and solar cells to the soft domain of chemistry and biology under the guise of chemical reactions in solution, biomimetic systems, and quantum biology. Quantitative analysis of radical pair phenomena has historically been successful by a few select groups. With this in mind, we present an intuitive open-source framework in the Python programming language that provides classical, semiclassical, and quantum simulation methodologies. A radical pair kinetic rate equation solver, Monte Carlo-based spin dephasing rate estimations, and molecule database functionalities are implemented. We introduce the kine-quantum method, a new approach that amalgamates classical rate equations, semiclassical, and quantum techniques. This method resolves the prohibitively large memory requirement issues of quantum approaches while achieving higher accuracy, and it also offers wavelength-resolved simulations, producing time- and wavelength-resolved magnetic field effect simulations. Model examples illustrate the versatility and ease of use of the software, including the new approach applied to the magnetosensitive absorption and fluorescence of flavin adenine dinucleotide photochemistry, spin-spin interaction estimation from molecular dynamics simulations on radical pairs inside reverse micelles, radical pair anisotropy inside proteins, and triplet exciton pairs in anthracene crystals. The intuitive interface also allows this software to be used as a teaching or learning aid for those interested in the field of spin chemistry. Furthermore, the software aims to be modular and extensible, with the aim to standardize how spin dynamics simulations are performed.

Biomarkers in Colorectal Cancer: Actual and Future Perspectives.

Biomarkers in colorectal cancer (CRC) are of great interest in the current literature due to improvements in techniques such as liquid biopsy and next-generation sequencing (NGS). However, screening methods vary globally, with multi-target stool DNA (mt-sDNA) predominantly used in the USA and, more recently, the Cologuard Plus; biomarkers such as the Galectins family and septins show promise in early detection. Gut microbiome assessments, such as Fusobacterium nucleatum, are under intense exploration. Diagnostic tests, such as circulating DNA analysis via NGS, exhibit effectiveness and are being increasingly adopted. Circulating tumor cells emerge as potential alternatives to traditional methods in terms of diagnosis and prognosis. Predictive biomarkers are well established in guidelines; nonetheless, with the aid of machine learning and artificial intelligence, these biomarkers may be improved. This review critically explores the actual dynamic landscape of CRC biomarkers and future, promising biomarkers involved in screening, diagnosis, and prognosis.

Foreign Languages and Aesopianisation: When the Popularity of Fables Unlocks Spanish

Purpose. This article explores the concept of the ‘Aesopianisation’ of other languages, focusing on the idea of using Aesop’s fables as a language learning aid. The fable of “The Fox and the Grapes” serves as an example of the widespread popularity of Aesop's timeless stories, making them an ideal resource to unlock related languages, such as Spanish. Methodology. The integration of beloved fables into reading comprehension and classroom discussion captivates students' imaginations and may help to solve one of the most daunting challenges in education: mastering analytical reading. Employing content analysis, this article delves into the application of narrative popularity effect (NPE) (1), linguistic context predictability (LCP) (2), lexical interlingual cognates (LIC) (3), and collocational patterns (CP) (4) as four useful linguistic tools to solve one of the most daunting educational challenges: unlocking a foreign language through detailed analytical reading. Results. The findings reveal a remarkable ability of these tools to extract the lexicon and structures from ten selected popular fables in Spanish, underscoring the potential efficacy of this approach in language learning. Conclusions. The study suggests that combining linguistic and cultural awareness can be a powerful tool for learning foreign languages, demonstrating that the ‘Aesopianisation’ of a language is indeed possible.

Maximizing Potential : 5W+1H Reading Comprehension Strategy for Student with Moderate Intellectual Disability

This study aims to enhance the reading comprehension skills of elementary school students with moderate intellectual disabilities through a single-subject method. In this study, the researchers use the 5W + 1H strategy to help students understand the meaning of the text. The research data was collected using observation guidelines, which then will be analyzed by using pretest-posttest techniques to assess the subject’s reading comprehension skills improvements. Teaching the 5W + 1H principle - which emphasized the question words why and how using visual images and keywords - was found to be effective in enhancing the subject’s reading comprehension. This finding also explained that this method could maximize the potential of students with moderate intellectual disabilities. The instruction on the question words why and how was particularly effective in increasing the subject's understanding of questions as well as leading him to provide correct and contextually appropriate responses. However, using visual images as a learning aid, especially for why and how questions, seemed less effective, as evidenced by the subject's reliance on keywords within the sentence. In the future, this strategy can be employed by educators to enhance reading comprehension skills for students with moderate intellectual disabilities.

Drama as an Aid in Academic Learning and Creative Writing: The CBS Radio Mystery Theater

A comprehensive radio series of 1,399 episodes which originally ran seven nights a week from January 1974 to December 1982. The series dealt with a very large expanse of subject matter, not only in classic and modern literature and history, but also at times featured basic facts in the areas of the sciences including chemistry, medicine, astronomy and physics. As a result, the series served, and continues to serve as an effective educational tool in addition to being a source of entertainment very similar in style to the audiobook. It also serves as a virtual template for the study of the art of storytelling and creative writing.

&lt;b&gt;Insights From the Frontlines: Students' Perceptions of Teaching Methods in a Nigerian Medical School &lt;/b&gt;

Background The teaching skills of the teachers impact the learning outcomes, and it is expected that learning can be enhanced through appropriate instructional strategies that will optimally help the students. An understanding of student’s perception of the available teaching methods will provide insight into what the challenges are, and how this information can be used to further optimize learning outcomes. Methods A qualitative phenomenology study using focus group discussions among 41 clinical medical students in a developing Nigerian medical school. An inductive thematic analysis was performed on the transcribed recorded data from the group discussions. Results Six themes emerged: participation, clarity and applicability, encouragement and feedback, teaching aids, students-teachers relationship, and learning environment. Students preferred problem-based learning and small group teaching, perceiving didactic lectures as lengthy and boring. They emphasized the need for teachers to use real-world examples, provide feedback, and adopt student-centered approaches. The majority of students preferred visual learning aids but noted inadequate infrastructure and resources for their preferences. Conclusions This study highlights the importance of student-centered teaching methods, incorporating visual aids and problem-based learning, to enhance engagement and retention. Teachers should adapt their instructional strategies to cater to diverse learning styles and promote interactive learning. The study suggests retraining clinical teachers to adopt student-centered approaches and utilize available resources effectively. By prioritizing student feedback and adopting inclusive teaching methods, medical educators can optimize learning outcomes and prepare students for the demands of healthcare practice. Keywords: medical, students, perceptions, teaching, methods.

Reevaluating student-centred education: uncovering learning difficulties stemming from empiricist epistemological assumptions

ABSTRACT This paper demonstrates that recurrent difficulties students encounter in learning subject-matter knowledge can be traced, in part, to assumptions about how students best learn knowledge that significantly shape instructional approaches. First, I review the significant influence of empiricist epistemological assumptions on education, covering student-centred pedagogical principles and instructional methods applied in progressive, constructivist, and conventional education. Empiricist epistemological assumptions presume that students learn best by relying primarily on and directly building upon their existing knowledge, experiences, and reasoning, particularly those familiar from everyday life. These assumptions have shaped pedagogical principles and methods such as relying on students' preinstructional knowledge and reasoning, concrete experiences, direct observations, or concrete visual images for learning. Next, I review evidence that empiricist-informed instructional applications often induce learning difficulties, such as erroneous inferences stemming from students' preinstructional knowledge, difficulty understanding content that diverges from students' prior knowledge, and confusion between concrete supports and abstract concepts. By tracing these difficulties to empiricist epistemological assumptions, this paper employs a genealogical epistemological analysis, which tracks the influence of epistemological assumptions on education across several levels, from pedagogical principles to instructional methods, down to students' learning. This analysis (a) explains the roots of certain learning difficulties and aids in anticipating them, (b) challenges pedagogical approaches by questioning their epistemological foundations, and (c) examines how the influence of problematic assumptions is connected to alignment with internationally promoted educational purposes. The influence of epistemological assumptions on education is significant yet understudied. Thus, the genealogical epistemological analysis proves crucial to critically analyze education.

Occurrence, distribution and description of Harmonia dimidiata (Fabricius), a predacious Coccinellid from West Bengal, India

Aim: To provide information about the occurrence and distribution of Harmonia dimidiata from West Bengal and facilitate the identification of species based on morpho-taxonomy. Methodology: Survey was done in different agro-climatic zones of West Bengal. Specimens were procured from their associated host plants, brought to the laboratory and investigated for taxonomic characters. Results: The morpho-taxonomy of H. dimidiata, as well as its host record, and distribution, were fully explained in the present investigation. It is most common in hill, terai, and old alluvial zone of West Bengal. They have been observed preying on Rhopalosiphum maidis (Fitch) in corn and Aphis gossypii (Glover). Interpretation: H. dimidiata population were recorded during survey from four different agro-climatic zones of West Bengal. They were observed to be preyed upon A. gossypii and R. maidis. The information about the biodiversity of H. dimidiata and their role as predator of numerous agriculturally important crop pests are extremely valuable that enrich our knowledge and immensely help in devising a pest management programme considering them as an important biocontrol agent. Furthermore, research on their biodiversity aids in learning about the predaceous behaviour in connection with the pest and crop populations, their reproduction and occurrence. This information is indeed praiseworthy while exploiting the ladybird species, H. dimidiata for a commercial biocontrol operation. Key words: Coleoptera, Coccinellidae, Harmonia dimidiata, Predaceous, West Bengal

Disclosures &amp; Disclaimers: Investigating the Impact of Transparency Disclosures and Reliability Disclaimers on Learner-LLM Interactions

Large Language Models (LLMs) are increasingly being used in educational settings to assist students with assignments and learning new concepts. For LLMs to be effective learning aids, students must develop an appropriate level of trust and reliance on these tools. Misaligned trust and reliance can lead to suboptimal learning outcomes and reduced LLM engagement. Despite their growing presence, there is a limited understanding of achieving optimal transparency and reliance calibration in the educational use of LLMs. In a 3x2 between-subjects experiment conducted in a university classroom setting, we tested the effect of two transparency disclosures (System Prompt and Goal Summary) and an in-conversation Reliability Disclaimer on a GPT-4-based chatbot tutor provided to students for an assignment. Our findings suggest that disclaimer messages included in the responses may effectively mitigate learners' overreliance on the LLM Tutor in the presence of incorrect advice. Disclosing System Prompt seemed to calibrate students’ confidence in their answers and reduce the occurrence of copy-pasting the exact assignment question to the LLM tutor. Student feedback indicated that they would like transparency framed in terms of performance-based metrics. Our work provides empirical insights on the design of transparency and reliability mechanisms for using LLMs in classrooms.

PENERAPAN PEMBELAJARAN PAI BERBASIS DIGITAL LEARNING DI SMP ISLAM PARLAUNGAN WARU SIDOARJO

This research aims to examine the application of digital-based learning in increasing student creativity at SMP Islam Parlaungan Waru Sidoarjo, Sidoarjo. This research is qualitative research, while data collection uses observation, interviews and documentation methods. The research results show that PAI teachers in delivering lesson material in the classroom use digital media such as PowerPoint, learning videos, and use smartphones as learning aids. By using digital media in the teaching and learning process, it can be concluded that, one of the teacher's methods is to enliven the class atmosphere so that discussions occur between students, making it easier for teachers to convey the material and students easily understanding the material. PAI subject teachers use digital media in their learning by displaying PowerPoint slides and interesting learning videos. By using digital media, the teaching and learning process becomes more effective and efficient. The use of PPT and learning videos can help students understand the material better and spark creative ideas, while smartphones facilitate wider access to information and interaction. Thus, implementing digital-based learning at SMP Islam Parlaungan Waru Sidoarjo can be an effective strategy for increasing student creativity, which can support more active and innovative learning.