Student authentication and authorship checking systems are intended to help teachers address cheating and plagiarism. This study set out to investigate higher education teachers’ perceptions of the ...prevalence and types of cheating in their courses with a focus on the possible changes that might come about as a result of an increased use of e-assessment, ways of addressing cheating, and how the use of student authentication and authorship checking systems might impact on assessment practice. This study was carried out within the context of the project TeSLA (an Adaptive Trust-based e-assessment System for Learning) which is developing a system intended for integration within an institution’s Virtual Learning Environment (VLE) offering a variety of instruments to assure student authentication and authorship checking. Data was collected at two universities that were trialling the TeSLA system, one in Turkey, where the main modes of teaching are face-to-face teaching and distance education, and one in Bulgaria, where the main modes of teaching are face-to-face teaching and blended learning. The study used questionnaires and interviews, building on existing TeSLA project evaluation activities and extending these to explore the specific areas we wished to examine in more depth.
In three of the four contexts cheating was seen by teachers as a serious and growing problem, the exception was the distance education context where the teachers believed that the existing procedures were effective in controlling cheating. Most teachers in all four contexts expected cheating to become a greater problem with increased use of e-assessment. Student authentication was not seen as a major problem in any of the contexts, as this was felt to be well controlled through face-to-face proctored assessments, though the problem of assuring effective authentication was seen by many teachers as a barrier to increased use of e-assessment. Authorship checking was seen as a major issue in all contexts, as copying and pasting from the web, ghost writing and plagiarism were all reported as widely prevalent, and authorship checking was seen as becoming even more important with increased use of e-assessment. Teachers identified a third category of cheating behaviours, which was the accessing of information from other students, from written materials, and from the internet during assessments.
Teachers identified a number of approaches to addressing the problem of cheating: education, technology, assessment design, sanctions, policy, and surveillance. Whilst technology was not seen as the most important approach to prevention, student authentication and authorship checking systems were seen as relevant in terms of reducing reliance on face-to-face proctored examinations, and in improving the quality of assessment through supporting the employment of a wider range of assessment methods. The development of authorship checking based on computational linguistic approaches was an area of particular interest. Student authentication and authorship checking systems were not seen as being able to address the third category of cheating behaviours that the study identified.
Artificial intelligence has impacted education in recent years. Datafication of education has allowed developing automated methods to detect patterns in extensive collections of educational data to ...estimate unknown information and behavior about the students. This research has focused on finding accurate predictive models to identify at-risk students. This challenge may reduce the students’ risk of failure or disengage by decreasing the time lag between identification and the real at-risk state. The contribution of this paper is threefold. First, an in-depth analysis of a predictive model to detect at-risk students is performed. This model has been tested using data available in an institutional data mart where curated data from six semesters are available, and a method to obtain the best classifier and training set is proposed. Second, a method to determine a threshold for evaluating the quality of the predictive model is established. Third, an early warning system has been developed and tested in a real educational setting being accurate and useful for its purpose to detect at-risk students in online higher education. The stakeholders (i.e., students and teachers) can analyze the information through different dashboards, and teachers can also send early feedback as an intervention mechanism to mitigate at-risk situations. The system has been evaluated on two undergraduate courses where results shown a high accuracy to correctly detect at-risk students.
Openness in education has received significant attention in recent years. To comprehend this concept in education ecosystems thoroughly, a longitudinal study is crucial, offering a comprehensive ...perspective of its evolution. The study utilizes bibliometric techniques, social network analysis, and text mining to investigate openness from its origin to the present day. The research highlights that the idea of openness, initially linked to open universities, has expanded into broader education ecosystems due to advancements in digital technologies, especially around the turn of the 21st century. Embracing open access and open scholarship as new business models is essential to consolidate openness in education. Additionally, distance education, online learning, and educational technology play vital roles as catalysts for openness in education, providing a holistic understanding of the concept.
Learning analytics is quickly evolving. Old fashioned dashboards with descriptive information and trends about what happened in the past are slightly substituted by new dashboards with forecasting ...information and predicting relevant outcomes about learning. Artificial intelligence is aiding this revolution. The accessibility to computational resources has increased, and specific tools and packages for integrating artificial intelligence techniques leverage such new analytical tools. However, it is crucial to develop trustworthy systems, especially in education where skepticism about their application is due to the risk of teachers’ replacement. However, artificial intelligence systems should be seen as companions to empower teachers during the teaching and learning process. During the past years, the Universitat Oberta de Catalunya has advanced developing a data mart where all data about learners and campus utilization are stored for research purposes. The extensive collection of these educational data has been used to build a trustworthy early warning system whose infrastructure is introduced in this paper. The infrastructure supports such a trustworthy system built with artificial intelligence procedures to detect at-risk learners early on in order to help them to pass the course. To assess the system’s trustworthiness, we carried out an evaluation on the basis of the seven requirements of the European Assessment List for trustworthy artificial intelligence (ALTAI) guidelines that recognize an artificial intelligence system as a trustworthy one. Results show that it is feasible to build a trustworthy system wherein all seven ALTAI requirements are considered at once from the very beginning during the design phase.
The advent of Web 2.0 technologies transformed online networks into interactive spaces in which user-generated content has become the core material. With the possibilities that emerged from Web 2.0, ...social networking sites became very popular. The capability of social networking sites promises opportunities for communication and interaction, especially for distance education students who are separated from their teachers, learning resources and other students in terms of time and/or space. Within this perspective, the aim of the study is to investigate distance education students’ perceptions and preferences regarding use of social networking sites for communication and interaction purposes. In this context, the study employed a quantitative cross-sectional methodology. Research findings were derived from a sample of 2065 distance education students and the data were gathered through an online questionnaire. The research findings indicate that social networking sites (SNSs) can be used to support social learning processes.
The aim of this study was to identify students’ perceptions on cheating and plagiarism and trust in e-assessment according to their assessment experience and mode of learning as well as exploring ...their concerns in e-assessment. Participants were 952 students from two public universities in Turkey and Bulgaria. The study was designed as a cross-sectional survey. A questionnaire consisting of closed and open-ended questions was applied to collect data. Descriptive statistics, t-test, ANOVA and thematic analyses were performed. According to the results, no significant difference was found on students’ perceptions towards cheating and plagiarism and their feelings of trust in e-assessment regarding students’ prior e-assessment experience. However, there was a significant difference on students’ perceptions towards cheating and plagiarism and their feelings of trust in e-assessment regarding the mode of learning they are involved in. In addition, students’ concerns about e-assessment were explored in details in the paper.
Though first appeared in 1971, digital book technology has evolved especially since 2000s and it is relatively a new research area. Therefore, to better understand this phenomenon, a quantitative ...survey research was conducted in 2015 spring term in a state university in Turkey. The objective of the study is to explain current state of digital books within post-graduate students’ perspectives and to identify post-graduate student’s perceptions, attitudes and preferences related to digital books. In this regard, this research presents results of the survey. A total of 135 post-graduate students responded the questionnaire. The data regarding use of digital books in addition to demographics was collected through an online questionnaire and the findings were analyzed through descriptive statistics. In this sense, post-graduate students’ use of digital books, purposes to use, preferred devices, and most used features of digital books were examined. In addition to these questions, reasons not to use digital books and post-graduate students’ future attitude whether to use digital books or not were further investigated. Additionally, research directions for future implications were provided.
Previous studies have described many scales for measuring self-regulation; however, no scale has been developed specifically for self-paced open and distance learning environments. Therefore, the aim ...of this study is to develop a scale for determining the self-regulated learning skills of distance learners in self-paced open and distance learning courses. Participants of this study were 1279 distance learners who were part of self-paced distance learning courses in a public open and distance teaching university in Turkey. The items of the scale were prepared based on the literature review, expert opinions, and learner questionnaires. The items of the scale were reduced from 62 to 30 after expert opinions and validity and reliability analyses. For the validity of the scale, the exploratory and confirmatory factor analyses were conducted. The total variance was found to be 58.204%. The Cronbach’s alpha coefficient calculated for the reliability of the scale was found to be .937. Five factors composed of goal setting, help seeking, self-study strategies, managing physical environment, and effort regulation emerged in the 30-item scale. Thus, it was concluded that the scale has a high validity and reliability. This scale is intended to help teachers and instructional designers in developing strategies that will enable learners to either enhance their existing self-regulated learning skills or help them to acquire new skills in self-paced open and distance learning environments.
Artificial intelligence (AI) has penetrated every layer of our lives, and education is not immune to the effects of AI. In this regard, this study examines AI studies in education in half a century ...(1970–2020) through a systematic review approach and benefits from social network analysis and text-mining approaches. Accordingly, the research identifies three research clusters (1) artificial intelligence, (2) pedagogical, and (3) technological issues, and suggests five broad research themes which are (1) adaptive learning and personalization of education through AI-based practices, (2) deep learning and machine Learning algorithms for online learning processes, (3) Educational human-AI interaction, (4) educational use of AI-generated data, and (5) AI in higher education. The study also highlights that ethics in AI studies is an ignored research area.
An Intelligent Nudging System to Guide Online Learners Rodríguez, M. Elena; Guerrero-Roldán, Ana Elena; Baneres, David ...
International review of research in open and distance learning,
02/2022, Letnik:
23, Številka:
1
Journal Article
Odprti dostop
This work discusses a nudging intervention mechanism combined with an artificial intelligence (AI) system for early detection of learners’ risk of failing or dropping out. Different types of ...personalized nudges were designed according to educational principles and the learners’ risk classification. The impact on learners’ performance, dropout reduction, and satisfaction was evaluated through a study with 252 learners in a first-year course at a fully online university. Different learners’ groups were designed, with each receiving a different set of nudges. Results showed that nudges positively impacted the learners’ performance and satisfaction, and reduced dropout rates. The impact significantly increased when different types of nudges were provided. Our research reinforced the role of AI as useful in online, distance, and open learning for providing timely learner support, improved learning experiences, and enhanced learner-teacher communication.
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