A Method for Recommending Sports Network Course Resources Based on Collaborative Filtering Technology

In the process of online course resource recommendation, the output of recommendation results is often unstable. Therefore, a physical education online course resource recommendation method based on collaborative filtering technology is proposed. Firstly, the learning preference of e-learners is calculated, the frequency index of the word frequency-inverse document is defined, the correlation between courses is reflected, and the specific needs of students for PE online course resource recommendation are understood. Then, the collaborative filtering recommendation algorithm is used to generate the similarity matrix and correlation matrix, update the edge characteristics of sports online curriculum resources, collect and refine the hidden index of sports online curriculum resources, optimize the prediction rules of the neighborhood of the most similar teaching unit, and complete the recommendation of sports online curriculum resources. Experimental results show that, for 1000 keywords, the method has the highest single average matching degree, the recommendation process is stable, and the F1 value is more than 0.9, and the practical application is ensured.

The Effectiveness of Self-Instructional Video vs. Classroom Teaching Method on Focused Assessment With Sonography in Trauma Among House Officers in University Hospital

Background: The aim of this study was to compare the effectiveness of self-instructional-video (SIV) and classroom training method (CTM) in learning Focus-Assessment with Sonography-in-Trauma (FAST) among house officers (HO).Method: A randomized controlled study involving house officers working in the university hospital in Malaysia was conducted where participants were randomized into SIV group (intervention) and CTM group (control). Each group had to undergo a 4 h hands-on training. The intervention group has undergone self-training using the video material without any facilitation while the control group received lecture and hands-on training with facilitators. Participants' performance was assessed using a validated Objective Structured Clinical Examination checklist for landmark identification and interpretation of images generated. Learning preference and confidence level were also assessed.Result: A total of 33 HO were enrolled in this study. Marks obtained in image acquisition by the intervention and control were 25.3 (SD = 5.3) and 25.6 (SD = 2.3) p > 0.05, respectively. While in image interpretation, the mean score for the intervention and control group was 10.3 (SD 1.7) and 9.8 (SD = 1.7) p > 0.05, respectively. Overall performance assessment, showed the intervention group obtained 35.6 (SD = 5.9) compared to control 35.3 (SD = 3.4), p > 0.05. Based on pre-specified determinant these scores difference falls within the 10% of non-inferiority margin. The absolute difference between both groups was 0.3 (CI = −3.75 to 3.21, p = 0.871), which proves non-inferiority but not superiority. In terms of learning preference and confidence to perform FAST, most of the participants preferred the control group approach.Conclusion: The SIV method is as effective as the CTM for learning FAST among the house officers and served as an alternative to classroom teaching. However, this technique needs improvement in promoting their confidence and preference. Perhaps incorporating a feedback session after going through the SIV would improve the confidence.

Understanding the Learning Styles of Physiotherapy Students

Physiotherapy students have wide range of diversity in their learning preferences therefore this has been always a challenged for the teachers to meet their demands. Understanding learning style preference encourages both students and teachers to continuously update themselves resulting in greater educational satisfaction. Study was performed to find out differences of learning preferences from first to final year physiotherapy students of LJ Institute of physiotherapy, Ahmedabad, Gujarat. Total 220 physiotherapy students from all four years were invited to participate in study, out of which 161 students (male: 49, female: 112) voluntarily participated in study. A web-based survey was implemented in this study which included VARK questionnaire and we found 72.7% students have multimodal learning style and kinaesthetic was the preferred sensory modalities of learning for most of the years but final year also showed more aural learning. Most of the male students in our study showed kinaesthetic learning and previous year academic performance also has influence on learning preference. Key words: VARK, learning style, Physiotherapy.

Children With More Uncertainty in Their Intuitive Theories Seek Domain-Relevant Information

How do changes in learners’ knowledge influence information seeking? We showed preschoolers ( N = 100) uncertain outcomes for events and let them choose which event to resolve. We found that children whose intuitive theories were at immature stages were more likely to seek information to resolve uncertainty about an outcome in the related domains, but children with more mature knowledge were not. This result was replicated in a second experiment but with the nuance that children at intermediate stages of belief development—when the causal outcome would be most ambiguous—were the most motivated to resolve the uncertainty. This effect was not driven by general uncertainty at the framework level but, rather, by the impact that framework knowledge has in accessing uncertainty at the model level. These results are the first to show the relationship between a learning preference and the developmental stage of a child’s intuitive theory.

Online Learning Effectiveness During the COVID-19 Pandemic: A Case Study of Saudi Universities

This paper is set out to explore the students’ attitudes towards online learning effectiveness using theBlackboard platform in three Saudi public universities (Taibah, Hail, and Al-Baha) during COVID-19pandemic. It examines the main learning activities which ensure the achievement of education qualityduring unprecedented online learning. These activities are online learning preference, efficiency,participation, achievements, success, and assigned assessment tasks. The survey-based questionnairemethod was used to elicit students’ responses regarding online learning effectiveness. The total numberof students who participated in the survey is 333 (entirely regular bachelor’s courses in differentmajors). The main section of the questionnaire contains several questions about leading online learningactivities. The coefficient relation of the p-value is highly correlated when tested using Pearson’s rand Spearman’s. The score of Cronbach’s Alpha is 0.93, which indicates (greater internal consistency)an acceptable level of reliability. The overall mean is 0.20, and the standard deviation for the sampleis 0.095. The findings positively emphasize the significant influence of online learning on students’academic achievements in most learning factors except in an assigned assessment factor, which isstill problematic in the online learning process.

THE EFFECTIVENESS OF ONLINE-BASED LEARNING IN JAVA PROGRAMMING LANGUAGE: STUDENT PERCEPTIONS AND PERFORMANCE

This research aims to explore the effectiveness of learning Java programming language using online-based learning compared to traditional-based learning towards undergraduate students in Universiti Utara Malaysia (UUM). Similar types of learning materials in the form of slides, notes and books are used with additional forms of assessments to substitute the final exam. The main difference is in the learning approaches which have been switched to online based via various platforms depending on the suitability and preference of the students. This research focuses on identifying and analyzing certain aspects from the students’ perceptions, which are the students’ (1) learning preference; (2) learning engagement; (3) learning assessment, and in terms of their overall (4) satisfaction towards the learning process. This research uses a quantitative approach through the questionnaire as the survey instrument, involving 31 students. The data is analyzed using descriptive statistics (percentage frequency distribution, mean, and standard deviation). Findings show that despite using online-based learning, 48.39% obtained marks above 80% in Lab Test 2, which is doubled compared to the previous test, Lab Test 1, 25.81%. This indicates that while students prefer traditional-based learning, they are able to perform better through online-based learning.

Learning preference: development in smart learning environments

Purpose The purpose of this study is to conduct a systematic review to understand state-of-art research related to learning preferences from the aspects of impacts, influential factors and evaluation methods. Design/methodology/approach This paper uses the systematic synthesis method to provide state-of-the-art knowledge on learning preference research by summarizing published studies in major databases and attempting to aggregate and reconcile the scientific results from the individual studies. The findings summarize aggregated research efforts and improve the quality of future research. Findings After analyzing existing literature, this study proposed three possible research directions in the future. First, researchers might focus on how to use the real-time tracking mechanism to further understand other impacts of learning preferences within the learning environments. Second, existing studies mainly focused on the influence of singular factors on learning preferences. The joint effects of multiple factors should be an important topic for future research. Finally, integrated algorithms might become the most popular evaluation method of learning preference in the era of smart learning environments. Research limitations/implications This review used the search results generated by Google Scholar and Web of Science databases. There might be published papers available in other databases that have not been taken into account. Originality/value The research summarizes the state-of-art research related to learning preferences. This paper is one of the first to discuss the development of learning preference research in smart learning environments.

Learning Styles and Online Tools

Very few studies in the existing literature elaborated about the learners learning preference and their preferred ICT tools while they were engaging in an online course. In order to fill this gap, this chapter presents different learning styles, which are exhibited by the learners in an online environment. It identifies myriad ICT (information and communication technology) tools and shows association between learning styles and respective ICT tools. It has four main broad areas to discuss: provides general importance of incorporating ICT tools in an online environment; presents four types of learners in an online context, which are characterized by following previous theoretical framework; identifies different learning activities, which are preferred by the four learners; and provides ICT tools along with their web address that are linked with online activities. This chapter shows possible implication towards online education and practices.