Ensuring Optimal Accessibility of Online Learning Resources

The occurrence of corona virus disease in 2019 (Covid-19) pandemic with its negative consequences on various sectors including education up till now has led to the increase in the necessity to use online learning resources and platforms for teaching and learning especially in higher education institutions (HEIs) in various countries. This research paper's major goal was to investigate the online learning attitude and online learning readiness of undergraduate accounting students in Nigerian public HEIs during the Covid-19 pandemic. The research participants consisted of 845 male and female undergraduate accounting students purposively selected from six HEIs. Study data was collected quantitatively with two online learning scales addressing students' online learning attitude and online learning readiness respectively. The study data were analysed with relevant statistical tests in the Statistical Package for the Social Sciences (SPSS, version 22) based on .05 level of significance criteria. The finding demonstrates significantly positive online learning attitude among the undergraduate accounting students from the studied HEIs during the Covid-19 pandemic. Finding also showed that the undergraduate accounting students' online learning attitude significantly related to their online learning readiness during the Covid-19 pandemic. The male and female undergraduate accounting students did not differ in their online learning attitude and online learning readiness. There were no significant differences in online learning attitude and online learning readiness among the undergraduate accounting students from the studied HEIs based on institution type (university, polytechnic and college of education). Nigerian HEIs and accounting departments should provide efficient online learning access and resources to these students and work towards bridging any existing institutional disparities in the availability and use of online learning facilities and resources.

Although several studies have evaluated online learning tools and resources, few have investigated how useful they are to students. This topic became even more relevant with “emergency remote learning” due to coronavirus disease 2019 (COVID-19). The present study was conducted at a state educational institution in Mexico that offers five university degrees. The objective was to differentiate the importance of online learning resources by degree and by employment status of the students. This quantitative, relational, cross-sectional study included 969 participants. Jamovi, SPSS, and RStudio were used to calculate descriptive statistics and to perform the Scheirer-Ray-Hare and Friedman tests. The results showed that the most important learning resources are lesson recordings, teacher explanations, instructional materials, and online demonstrations, whereas the least important are exams, videos, homework, and projects. These findings were consistent across the five degrees among students who are employed and those who are not. The results suggest that educational resources should be used according to their importance for student learning.

Digitisation represents one of the key directions of adult education and training in the post-COVID-19 times, but direct empirical evidence of its scope among learners is rather scarce after 2021. Therefore, the general aim of this article is to investigate the current state of the use of online learning platforms and resources in adult education and training throughout Europe. For this purpose, we utilise data from a dedicated survey in the Czech Republic, Germany, Sweden, and the United Kingdom (n = 4,000) from 2022, which cover a wide range of digitalisation as measured by the Digital Economy and Society Index (DESI). Our findings are consistent with DESI in the overall levels of online learning across the four countries. Beyond this, we provide two main findings. First, the patterns of digitalisation are different in formal (FAE) and non-formal adult education (NFE). We identify two corresponding modes of platformization based on how and how much online learning platforms and resources are used. Second, factors of participation in online learning differ in some regards from factors of participation in AET in general. Therefore, online learning seems to constitute a new layer mediating participation in AET, possibly introducing new forms of inequalities.

This article aims to analyze the preference and accessibility that determine the students' behavioural appreciation in using learning resources towards the Open Educational Resources (OER) system owned by the Universitas Terbuka (UT), a so-called SUAKA-UT. It used qualitative research methods with descriptive percentage analysis. Furthermore, the instrument employed a Sakal Likert questionnaire and limited interviews. The research population was a non-basic educational program, with the random sampling technique by selecting 123 students. The following sample details: 35 students in Makassar City, 19 Students in Sidrap Regency, 23 students in Tana Toraja Regency, 23 Students in Selayar Regency, and 23 students in Luwu Timur Regency. The results showed that the preference for online sources and accessibility is in the excellent category and had an average score of 4.10 out of ten SUAKA-UT service questions. They showed that, generally, the respondents strongly agree with the available learning resources since they can meet the needs and accessibility of online learning resources. Preference for online learning resources is a supporting tool for achieving independent learning success. The utilization of SUAKA-UT in the working area of UT Makassar went very well in providing easy access to learning resources. The UT has met students' needs and expectations so they can study flexibly. SUAKA-UT has become a preferred and has excellent acceptance as an online learning resource among the students. To maintain the existence of open learning sources of UT (SUAKA-UT), as a distance learning university with the motto of "Making Higher education," it must consistently innovate and update its online learning resources.

With the advent of the digital era, the quantity and variety of online higher education learning resources have expanded rapidly. The efficient adaptation of suitable resources to meet the needs of learners with specific requirements has become crucial for improving learning outcomes. Although current online learning resource recommendation systems have made some progress in matching resources, they still face challenges related to the inadequate integration of resource features and a superficial understanding of learners’ needs. These challenges hinder the achievement of personalized and precise matching, affecting learners’ study efficiency and the effective utilization of educational resources. This study first analyzes the importance of adapting online higher education learning resources and the limitations of existing research. Subsequently, a novel neural network optimization strategy is proposed. The research comprises two main parts. Firstly, the self-attention-convolutional neural network (SA-CNN) model is employed for the deep integration of the content features of online learning resources. This aims to enhance the comprehensiveness of resource descriptions. Secondly, a deep-metric attention model is introduced to accurately model and adapt to learners’ needs. This approach not only optimizes the feature representation of learning resources but also enhances the sensitivity and accuracy of the recommendation system towards learners’ requirements. This study is of significant importance for improving the performance of higher education online learning resource recommendation systems. It also provides new insights into the construction of personalized learning paths and ensuring the balanced allocation of educational resources.

GAME PLAY IN VOCATIONAL TRINING AND ENINGEERING EDUCATION

The Editor, An extensive variety of learning resources are available to current radiology trainees [1,2] and in addition to traditional books and journals there now exists a wide range of electronic resources to promote further clinical education [1,2]. Use of electronic and internet applications have increased greatly over recent years and now provide a valuable information resource for radiologists in training. Online resources include websites such as Aunt Minnie, emedicine/Medscape, RSNA online and Imaging consult, as well as more exam focused subscription multiple choice question website such as PasTest and OnExamination. Online books and journals are now available and the Royal College also provides its own Radiology Integrated Training Initiative resource. We designed and distributed an anonymous online questionnaire to all London, Kent, Surrey and Sussex radiology trainees to examine the use of various online/electronic learning resources, including use of Radiology Integrated Training Initiative, for radiology trainees versus more traditional learning methods. We also set out to assess access to information technology (IT) resources within the Deanery. We received 136 compete responses from a total of 302 trainees (an overall response rate of 45%). 18% of respondents were preparing for FRCR Part 1, 28% for Part 2A, 22% for Part 2B and 32% had completed their exams. Despite such a wide range of electronic resources being available the single most popular learning format remained the traditional book (42), followed by Radiology Integrated Training Initiative online (24), paper journals (20) and electronic journals (14). Less popular resources included Emedicine (6), Aunt Minnie Online (6), RSNA Online (6), Online MCQ sites (6) and electronic books (4) (Figure 1). Figure 1 Single most preferred resource among respondents. Regarding online resources 39% of trainees used Emedicine/ Medscape weekly and 34% on a monthly basis. Only 18% had ever used Imaging Consult and two-thirds of these hardly ever used this resource. 75% had used Aunt Minnie online, with 51% using this resource monthly or more frequently. 66% had used RSNA online, with 43% using this monthly or more frequently. 46% had never used online MCQ resources (e.g. PasTest and OnExamination) and 38% had prepared for exams using MCQs passed on from other trainees. 64% used electronic books. 76% of respondents felt easier access to electronic journals would encourage online learning. 76 answered that less restrictive IT policies at their institution would encourage use of online resources. 66 felt that more time should be dedicated to online learning and 76 believed there should be more computers. Interestingly our data correlates with that of Rowell et al [1] who reported in their cohort of respondents that for reading journal articles, 67% prefer hard copy. They noted that the results of their survey indicated that, despite an increase in internet use and the perception that web based information is reliable, most radiologists still prefer traditional resources for radiological information and radiology education [1]. This is consistent with the London/KSS respondents who despite demonstrating use of a wide range of electronic and online learning resources, traditional methods, such as paper books remained the most popular. Yours etc., C J Burke R H Thomas D Fascia D Howlett S Heenan

Online learning platforms are prone to information overload, as they contain a huge number of diverse resources. To solve the problem, domestic and foreign scholars have focused their attention on personalized recommendation of learning resources. However, the existing studies perform poorly in the prediction of online learning paths, failing to clarify the overall knowledge system of students and the associations of resource knowledge. Therefore, this paper explores the collaborative filtering recommendation (CFR) of online learning resources (OLRs) based on knowledge association model. Firstly, the knowledge units were extracted from the semantic information of OLRs, and a knowledge association model was established for OLR recommendation. Next, a CFR algorithm was designed to couple semantic adjacency with learning interest, and used to quantify the semantic similarity of OLRs. The proposed algorithm was proved effective through experiments.

To effectively share and recommend knowledge, the online learning platform needs to deliver the most suitable and valuable learning resources to the demanders through the best path at a low cost. The existing studies mostly focus on the evaluation of knowledge flow ability and the extraction of knowledge classification features, but rarely tackle the knowledge flow evolution and network optimization in the light of the management of online learning resources (OLRs). To solve the problem, this paper explores the network optimization of OLRs from the perspective of knowledge flow. Firstly, the evolutionary game of the implicit knowledge flow in the OLR network was analyzed. In addition, an optimization model of OLRs was constructed, according to the evolutionary game mechanism for the implicit knowledge flow in the OLR network based on knowledge sharing, and the self-organizing hierarchical reconstruction. Finally, the network optimization effect was rated, and the network optimization was proved effective, with the management of music OLRs as an example.

People’s learning style is constantly changing together with the rapid development of information technology. Nowadays, online learning has become a common learning style, but online learning resource providers are also faced with the charging issue. Besides, a large number of studies have been made by scholars at home and abroad in this field. In this paper, the influence of middle school students’ self-efficacy on online learning resource purchase intention is analyzed, and the study comprises two stages. To be specific, in the first stage, the interview method is adopted to acquire related materials, and the grounded theory is also followed to reconstruct the theoretical research framework; in the second stage, the theoretical framework is empirically verified by the questionnaire. Then, it is found that middle school students’ self-efficacy affects the identity about online learning resources’ perceived quality and their purchase intention for online learning resources. At the same time, the teacher-student relation may also reinforce students’ purchase intention for online learning resources. Thus, it can be seen that online learning resources’ perceived quality and the intimate teacher-student relation have significant influence on middle school students’ purchase intention.

Aims: People with Intellectual Disability (PwID) have a reduced life expectancy in comparison to the general population, and constipation has been identified as a contributing factor to mortality by the Learning Disability Mortality Review. As part of a broader Quality Improvement project seeking out ways to reduce the rate of constipation for PwID it was recognised that robust and long-term education of carers was lacking.An online learning resource was created ‘Constipation in PwID for Social Carers’ to support those caring for PwID to recognise and appropriately signpost constipation-related issues.The learning resource was created by healthcare professionals, and it was therefore deemed necessary to undertake Quality Assurance of the module to ensure it was appropriate in both content and tone for support workers working in the social care sector. The final module was developed therefore with the input of those it was aiming to teach.Methods: Focus groups and feedback forms collected information regarding carer’s role, experience working with PwID, understanding and relevance of learning outcomes, overall quality, and suggested improvements of the learning resource. This was undertaken in focus groups, or on a one-to-one basis. Feedback forms were completed by 12 individual participants. Focus groups involved 20 participants total including community nurses, supported living managers, support workers, social workers, and occupational therapists.Results: Overall, the quality of the draft learning resource was rated ‘excellent’ and the general feedback was that it was appropriately pitched for carers. Aspects of the draft that helped with understanding content involved the use of scenario based interactive questions and visual aids. The information which was considered most useful included the Bristol Stool Chart, red light signs of constipation, and statistics on the prevalence of constipation in PwID.Suggested improvements for language were consistent terminology for PwID, and avoiding medical jargon to keep advice applicable in different settings. Participants asked for clear communication of the responsibility of support workers to escalate information to supported living management, GP, and NHS 111.Conclusion: Undertaking a robust Quality Assurance exercise for this online learning resource has ensured that language and terminology is appropriate for the target audience. Participants requested a clear message about how to escalate concerns. The next step will be to publish the resource online and evaluate its effectiveness in improving knowledge of constipation for carers of PwID.

The use of online learning resources as core components of university science courses is increasing. Learning resources range from summaries, videos, and simulations, to question banks. Our study set out to develop, implement, and evaluate research-based online learning resources in the form of pre-lecture online learning modules (OLMs). The aim of this paper is to share our experiences with those using, or considering implementing, online learning resources. Our first task was to identify student learning issues in physics to base the learning resources on. One issue with substantial research is conceptual understanding, the other with comparatively less research is scientific representations (graphs, words, equations, and diagrams). We developed learning resources on both these issues and measured their impact. We created weekly OLMs which were delivered to first year physics students at The University of Sydney prior to their first lecture of the week. Students were randomly allocated to either a concepts stream or a representations stream of online modules. The programme was first implemented in 2013 to trial module content, gain experience and process logistical matters and repeated in 2014 with approximately 400 students. Two validated surveys, the Force and Motion Concept Evaluation (FMCE) and the Representational Fluency Survey (RFS) were used as pre-tests and post-tests to measure learning gains while surveys and interviews provided further insights. While both streams of OLMs produced similar positive learning gains on the FMCE, the representations-focussed OLMs produced higher gains on the RFS. Conclusions were triangulated with student responses which indicated that they have recognized the benefit of the OLMs for their learning of physics. Our study shows that carefully designed online resources used as pre-instruction can make a difference in students’ conceptual understanding and representational fluency in physics, as well as make them more aware of their learning processes. In particular, the representations-focussed modules offer more advantages.

Online learning resources are learning resources that can be accessed online. As the basis for development is the relationship between the vision and mission of the State University of Malang as a reference university and changes to the curriculum at the State University of Malang which refers to life-based learning or a life-based curriculum. Researchers conduct research and development of learning innovation platforms or products in the form of websites as learning resources to become learning companion tools for students of the Special Education Department, Faculty of Education, State University of Malang. The level of feasibility of learning resources to accompany student learning is known through validation by material experts, validation by media experts, and trial use by students. The process of developing website-based online learning resources for students of the Department of Special Education, Faculty of Education, State University of Malang consists of assessment, design, development, implementation, and evaluation. The product result is a websitebased online learning resource. The website offers multimedia facilities with a combination of text, images, and videos as well as reference content in the form of journals and e-books.

This study attempts to reveal the intelligent recommendation mechanism of online learning resources. The “multimodal data fusion” aspect is adopted, illustrating online learning resource modeling, learning preference modeling, learning preference evolution, and referral engine smart design. Multimodal learning resources are key constituents of multidimensional intelligent recommendation services. The learner model that integrates multimodal preference data is the key to implementing smart recommendations. Learning preference evolution is a key factor in sustaining learner model robustness. The intelligent recommendation engine is the technical guarantee for developing an intelligent recommendation. Providing learning resources is an important part of online learning services, which mediate online learning processes. Intelligent recommendation, as an effective personalized servicing strategy, recommends differentiated, personalized, and precise learning resources to learners, thereby promoting the effectiveness of online learning performance. This study constructs a framework that reveals an intelligent recommendation mechanism for online learning resources.

As an important research topic in intelligent teaching systems, personalized recommendation services of learning resources can effectively solve the “information overload” problem and provide effective learning. However, the traditional learning resource recommendation technology mainly aims to improve recommendation accuracy and cannot effectively ensure the diversity and novelty of recommendation results. In this paper, the learning resource recommendation task is modelled with a multi-objective optimization problem. This paper proposes the Multi-Objective Evolutionary Algorithm-based online learning Resource Recommendation Model to balance the system’s accuracy, novelty, and diversity. The proposed model includes the following four steps: learning clustering, optimization goal setting individual representation, and genetic operator. According to the experimental results, this algorithm can improve the recommendation performance of online learning resources. Compared with the existing recommendation algorithms, more accurate, diverse, and novel learning resource recommendation results can be obtained with the proposed algorithm.