Developing and Implementing Retrieval Practice Questions to Reduce the DFW Rates (“D” or “F” or Withdraw) in an Undergraduate STEM Gateway Physiology Course
A Comparative Analysis of Multiple Representation Methods in Probability Learning in Mathematics Textbooks from Different Countries
A Study on Strengths and Weaknesses of Online Curriculum Transaction by Teacher Educators of Colleges of Education
The Role of Artificial Intelligence in Teaching and Learning: Perspectives of Learners, Teachers, and Administrators in Kerala Schools
Perceptions of M.Ed. Students on the Effectiveness and Accessibility of Online Learning in Higher Education
Towards Quality Higher Education in the Arab World: Challenges of the Present and Aspirations of the Future
Continuous Classroom Assessment At Primary Level
Edification Of Multimedia Resources: Aligning Technology For Student Empowerment
Improving Quality In Teaching Statistics Concepts Using Modern Visualization: The Design And Use Of The Flash Application On Pocket PCs
An Empirical Consideration Of The Use Of R In Actively Constructing Sampling Distributions
The Roles of Artificial Intelligence in Education: Current Progress and Future Prospects
The Role of Web-Based Simulations In Technology Education
Development Of Learning Resources To Promote Knowledge Sharing In Problem Based Learning
Fishing For Learning With A Podcast Net
An Orientation Assistant (OA) for Guiding Learning through Simulation of Electronics Technology in Technology Education
All universities are concerned with students earning D's, F's, or withdrawing (DFW) from their courses, particularly in STEM and gateway courses. One way to reduce this rate is to improve the instructional practices in a course by introducing learning strategies, including spaced and interleaved retrieval practice in formative assessments. U-behavior, a learning and teaching method that includes a formative assessment to help guide students into optimal spaced and interleaved retrieval practice, was implemented in a course with a high DFW rate. In part, this method requires students to complete practice questions as a part of their retrieval practice. This paper describes how practice questions were developed to enhance students' retrieval practice using the U-behavior method, aiming to reduce the overall DFW rate. Data was gathered at the end of the semester and compared to previous semesters to better understand the impact of this effort. The data showed an overall reduction of the DFW rate by 14.7%. Additionally, students who spaced and interleaved at the highest level showed significant improvement on their final exam, suggesting the potential benefits of improving student performance.
In this study, the 8th grade secondary school mathematics textbook approved by the ministry in Turkey was compared with the mathematics textbooks in France and the USA in terms of the use of the multiple representation method in the probability learning domain. Document analysis, one of the qualitative research methods, was used in the study, and the textbooks were selected using the typical case sampling method since the probability learning domain was examined within the same learning outcome. The 36 examples, exercises, activities, solved questions, and end-of-unit assessment questions in the Turkish textbook, 88 in the US textbook, and 96 in the French textbook were analyzed. This study utilized multiple representation types (Lesh et al.). According to the findings of the study, the most commonly used representation type in the Turkish mathematics textbook was algebraic representation (50%), the most commonly used representation type in the French mathematics textbook was verbal representation (25%), and the most commonly used representation type in the US mathematics textbook was algebraic representation (35%). In addition, the number of activities and questions in the French mathematics textbook was higher than in other countries, and the representation types were equally distributed. However, it is noteworthy that the Turkish textbook does not include graphic representations in the probability learning domain and uses very few tabular representations. In addition, the 5th grade mathematics textbook, which was prepared according to the new education model curriculum and started to be used in the 2024-2025 academic year, was examined, and changes in the probability learning domain were noted. It is recommended to increase the number of examples, activities, and questions in the probability learning domain and the use of multiple representations in the Turkish mathematics textbook.
The sudden transition to online education during the COVID-19 pandemic has significantly influenced how teacher educators in Colleges of Education deliver their curriculum. This study investigates the strengths and weaknesses experienced by teacher educators in conducting online curriculum transactions in Colleges of Education affiliated with the University of Mysore. The research aimed to evaluate educators' readiness, technological proficiency, and pedagogical adaptability in the digital learning environment. A descriptive survey method was adopted using a self- developed and validated SWOT Analysis Scale for Online Curriculum Transaction of Teacher Educators (SWOT-OCTTE). The instrument consisted of 64 items focused on strengths and weaknesses across 13 critical components. The tool was pilot tested and showed excellent internal consistency (Cronbach's alpha = 0.95). Data were collected from a stratified random sample of teacher educators from private colleges in the Mysore district. Results showed that 86% of respondents demonstrated key strengths in technological competency, institutional support, and professional ethics. However, 52% also reported critical weaknesses, especially in areas related to student engagement, online workload, and digital well-being. Independent samples t-tests and a one-way ANOVA indicated no statistically significant differences in strengths or weaknesses based on gender or academic stream. The findings highlight a dual trend: strong digital adaptation coexisting with pedagogical limitations. In this evolving educational context, teacher educators must develop both technological and instructional capabilities. The study points out that it requires targeted professional development, continuous digital training, and institutional strategies to bridge existing gaps. These insights contribute to enhancing the quality of teacher education and support policy-making in digital curriculum delivery.
This study explored the perceptions of learners, teachers, and administrators on the role of artificial intelligence (AI) in the higher secondary school education scenario of Kerala. The study was a comprehensive survey, and sample groups included 360 students, 60 teachers, and 5 administrators. Both qualitative methods and quantitative techniques are employed for data collection and analysis. The results indicate that students, teachers, and administrators expressed optimism about implementing AI in education. It is identified that, through the availability of educational resources and training, artificial intelligence has the potential to revolutionize the existing school education landscape. The results are supportive of recommending the government and policymakers publish guidelines to ensure the privacy and effective integration of artificial intelligence in education.
This study investigates how M.Ed. students observe online education and the usefulness of digital learning systems in higher education. It emphasizes learning results, digital accessibility, academic efficacy, and general satisfaction. Fifty M.Ed. students were given a structured questionnaire through Google Forms that included Likert-scale items. Through pilot testing and expert evaluation, the survey tool was verified. Perceptions were mainly positive, according to descriptive statistics: mean scores for learning outcomes were 16.0, digital accessibility and usability were 16.3, and academic effectiveness was 15.9. On the other hand, pleasure displayed more variation, with a lower mean of 13.9 and a standard deviation of 3.26, suggesting a range of experiences. Three major factors were found by exploratory factor analysis (EFA) to account for 39.3% of the variance: navigation difficulties, equity in access, and technical comfort and constraints. Bartlett's test (p = 0.019) and a KMO value of 0.538 confirmed the dataset's suitability for factor analysis. The findings suggest that while students recognize the academic benefits of online learning, challenges in usability and accessibility affect overall satisfaction. These results highlight the need for improved digital infrastructure, technical support, and inclusive design. Future research should include larger and more diverse samples to generalize findings and guide the development of effective online education systems in teacher education.
