e-learning
A. Fazel; A. Harandi
Abstract
Background and Objectives: The use of digital technology for teaching and learning has been discussed for decades, but now and in the post-Corona era, due to the problems of the COVID-19 pandemic, it has become the focus of many educational institutions. The effect of COVID-19, in a short period, brought ...
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Background and Objectives: The use of digital technology for teaching and learning has been discussed for decades, but now and in the post-Corona era, due to the problems of the COVID-19 pandemic, it has become the focus of many educational institutions. The effect of COVID-19, in a short period, brought about a huge change in the way of education and learning and even completely blocked some educational activities. As a result, education administrators have turned to other alternatives to replace face-to-face or traditional learning. Virtual education is one of the very important and serious programs proposed and carried out by educational institutions in that era, now and in the post-Corona period. The quality of designing and providing virtual education, like face-to-face education, depends on several inputs such as the teacher, learner, technological tools and education design, financial resources system, educational policies, and so on. Among the listed factors, the lecturers of these courses are of special importance. Therefore, according to the change in the teachers’ role, their previous skills can no longer be answered, and teachers, in addition to acquiring the necessary skills in the traditional learning environment, need empowerment in various fields, which is the most important step in achieving this important identification. Today, few universities can improve and develop without providing training courses to empower their faculty members, and this is doubly important in the post-Corona period when universities place a lot of emphasis on virtual education. This is because in the Corona and post-Corona period the emphasis on virtual education in higher education and increasing its use, requires special knowledge, skills, and abilities for professors To achieve this, identifying the skills of lecturers in virtual education, it seems essential and paying attention to these skills will lead to the growth of professors and as a result, improve the quality of virtual education. In particular, there is no significant study for the post-Corona period in the context of the research topic, and there is no study on identifying and explaining the teaching skills of teachers for virtual education using the methods of content analysis and fuzzy Delphi. Therefore, the present study aims to identify and explain the skills of academic staff members in virtual education in the post-Corona period in a precise manner using the approaches of content analysis and fuzzy Delphi and presenting a conceptual model.Materials and Methods: This research is an applied and descriptive research and the combined research methods of interview, content analysis, and fuzzy Delphi were used to collect and analyze information. The statistical population of the research is 20 experts and professors of the Shahid Bahonar University of Kerman. Data were collected through in-depth and semi-structured interviews. Then, all the interviews were analyzed with the method of content analysis, and the skills were extracted and identified. Then, skills were refined and explained in four survey stages using the fuzzy Delphi method.Findings: In the interview with the experts, two main questions were used to measure the skills and competencies of academic staff members for virtual education in the post-Corona period. The results of the qualitative section included 452 initial codes, which were reduced to 31 main codes and five main categories after data reduction and merging overlapping terms. These five main classes include moral-social, technical-technological, educational-learning, individual-managerial, and supervisory-supportive skills. Then, with a questionnaire, 31 identified skills were examined for refinement and confirmation in four stages. By examining the skills, the experts approved all of them with the fuzzy Delphi approach.Conclusions: In this study, it was determined that 31 skills are considered for virtual education teachers. In the meantime, we can safely say that 12 skills of social facilitation and appropriate counseling, conflict management, professional and ethical commitment, strategies and applications of learning theories, scholarly and research skills and knowledge sharing, skills to facilitate the teaching process, online lectures, encouraging and motivational skills, administrative and operational organizational skills, maintaining communication with students after completing the course, feedback, and monitoring learning activities, which were approved in the first round of the fuzzy Delphi method, are the most important skills of virtual education. Therefore, more emphasis should be placed on these skills in the post-Corona era in virtual courses.
Information literacy
S. Kalvari Janaki; A.S., Khakbaz; M. Pourjamshidi
Abstract
Background and Objectives: Information literacy refers to enabling individuals to determine when they need information and also having the ability to store, evaluate information, and using it effectively when needed. Teaching information literacy through the curriculum is one of the issues that has been ...
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Background and Objectives: Information literacy refers to enabling individuals to determine when they need information and also having the ability to store, evaluate information, and using it effectively when needed. Teaching information literacy through the curriculum is one of the issues that has been considered by curriculum planners in recent years. For this reason, educational systems in different countries have been trying different ways to equip people in communities with information literacy skills. Similarly, in our country, paying attention to teaching information literacy in curricula has been seen in the document of fundamental transformation of education. Two of the courses through which information literacy can be developed are Persian and writing courses. Therefore, the main purpose of this study was to investigate the status of information literacy in Persian and writing textbooks at the first year of high school.Methods: The research method in this study was content analysis with a quantitative approach. The statistical population included Persian and writing textbooks of the seventh, eighth and ninth grades of the first year of high school (academic year 2018-2019), on the whole comprised of six textbooks. The sampling method in this study was purposeful sampling method and the sample size was equal to the size of the population, because all six books were analyzed. The research instrument is the standard checklist of information literacy, extracted from the checklist of Lotfi Maher (2010). This checklist includes eight components of feeling the need for information and how to express it, gathering information and search strategies, understanding, internalizing and recording information, the correct usage of information, organizing information, evaluating and analyzing information, being successful and laying emphasis on social, economic and legal aspects of information. Indicators of descriptive statistics including frequency, frequency percentage, tables and graphs were used to analyze the data.Findings: The results showed that although quantitatively, on the average, about one third of the messages of all these textbooks (35.45%) had paid attention to the components of information literacy; the components of information literacy were not explicitly addressed, and information literacy content was more implicitly included in these books. Meanwhile, the status of writing textbooks in terms of information literacy components was better than the Persian textbooks, and grade 8 writing textbook with a frequency of 51.82 had the first rank and eighth grade Persian textbook with 23.84% had the lowest rate of information literacy messages among all the studied textbooks respectively. Among the components of information literacy, the fourth component (correct usage of information) was ranked first with the highest percentage and the eighth component (laying emphasis on the social, economic and legal aspects of information) was not considered at all. Very little attention was paid to the seventh (success) and the sixth (information evaluation) components.Conclusion: The results make it clear that reviewing these textbooks in terms of information literacy messages is necessary for curriculum planners. In this regard, it is suggested that texts or activities would be added to the content of these books to encourage students to conduct research and refer to various sources of information. It is also necessary to develop information literacy skills more explicitly in these books.
Learning Analytics
S.K. Banihashem
Abstract
Background and Objectives: Learning analytics is a new and promising field of study in education that seeks to capture, analyze and report data about learners and their learning environment for the purpose of optimizing learning and its environment. Data and analytics are the two main keywords for learning ...
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Background and Objectives: Learning analytics is a new and promising field of study in education that seeks to capture, analyze and report data about learners and their learning environment for the purpose of optimizing learning and its environment. Data and analytics are the two main keywords for learning analytics in which data is the feeder of analytics to provide evidence-based insights about teaching and learning. Although learning analytics has been of interest to many scholars during the last decade, little research has been done to provide a comprehensive framework of learning analytics. This study is aimed at identifying learning analytics components in education to provide a conceptual framework for optimizing learning. Methods: This is a qualitative study in which the design of the study is content analysis. The thematic analysis which is the research method suggested by Braun and Clarke was used in the following six steps: (1) familiarizing with collected data, (2) generating the initial codes, (3) searching for the themes and components, (4) reviewing the potential themes and components, (5) defining and naming the themes and components, and (6) reporting the results. In this study, 14 experts in the field of learning analytics were interviewed. Purposeful sampling method was used to select the participants. Moreover, the strategy for selecting these experts was based on the relationship between their theoretical and research activities. The reason why 14 experts were interviewed is the theoretical saturation which means data collection process continues until no new data is collected. That is to say that the theoretical saturation method was used to determine the sample size. To collect data, unstructured interview was performed. Data analysis was performed in three stages including open coding (line by line coding), axial coding (combining codes and developing a category of more general concepts) and selective coding the process of choosing one category to be the core category, and relating all other categories to this category). MAXQDA software version 2018 was used to run data analysis. The validity of the findings was assessed by the content validity index (CVI) and the reliability of the findings was determined based on Cohen’s kappa coefficient. Findings: The results showed that learning analytics is comprised of seven main components, including environment (background, culture, communication), objectives (optimization, learning, recognition, awareness of the process of learning, feedback, self-regulation, personalization, motivation, supervision, and assessment), stakeholders (learners, teachers, learning designers, administrators, and parents), data )meta-data, meaningful data, academic background data, academic data, performance data, interaction data, and psychological data), levels of analytics (descriptive, diagnostic, predictive, and prescriptive),], process (collection, analysis, report, and interpretation), and technique (analysis of social networks, clustering, categorization, prediction, regression, decision tree, factor analysis, discovery of association rules, discovering sequential patterns, and descriptive analysis], which altogether provide the conceptual framework of the learning analytics components in teaching for optimization of learning. Conclusion: Based on the findings of the study, the users of learning analytics in education can be recommended to consider these seven components when they are using them to optimize learning. Based on the findings, recommendations for future research and practical activities are made.
