Study success includes the successful completion of a first degree in higher education to the largest extent, and the successful completion of individual learning tasks to the smallest extent. Factors affecting study success range from individual dispositions (e.g., motivation, prior academic performance) to characteristics of the educational environment (e.g., attendance, active learning, social embeddedness). Recent developments in learning analytics, which are a socio-technical data mining and analytic practice in educational contexts, show promise in enhancing study success in higher education, through the collection and analysis of data from learners, learning processes, and learning environments in order to provide meaningful feedback and scaffolds when needed. This research reports a systematic review focusing on empirical evidence, demonstrating how learning analytics have been successful in facilitating study success in continuation and completion of students' university courses. Using standardised steps of conducting a systematic review, an initial set of 6220 articles was identified. The final sample includes 46 key publications. The findings obtained in this systematic review suggest that there are a considerable number of learning analytics approaches which utilise effective techniques in supporting study success and students at risk of dropping out. However, rigorous, large-scale evidence of the effectiveness of learning analytics in supporting study success is still lacking. The tested variables, algorithms, and methods collected in this systematic review can be used as a guide in helping researchers and educators to further improve the design and implementation of learning analytics systems.

Publisher: IEEE This document has been downloaded from MUEP (https://muep.mah.se) / DIVA (https://mau.diva-portal.org).

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<p class="0abstract"><span lang="EN-AU">Learning analytics show promise to support study success in higher education. Hence, they are increasingly adopted in higher education institutions. This study examines higher education experts’ views on learning analytics utilisation to support study success. Our main research question was to investigate how ready higher education institutions are to adopt learning analytics. We derived policy recommendations from an international systematic review of the last five years of learning analytics research. Due to the lack of rigorous learning analytics research and adoption in Germany, this study focusses on the German university context and examines how ready German university stakeholders are to adopt learning analytics. In order to validate the policy recommendations, we conducted an interview study from June to August 2018 with 37 German higher education stakeholders. The majority of participants stated that their institutions required further resources in order to adopt learning analytics but were able to identify what these resources were in order for successful implementation.</span></p>

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The supply and demand of entrepreneurship education at university level commenced in 1938. With the proven entrepreneurial effectiveness in economic development and the efforts of scholars, policymakers and other stakeholders, competencies in entrepreneurship are becoming a set of essential learning objectives. In the digital era, entrepreneurship education can be made available in an online and blended format. Thereby, this study presents a systematic analysis of research focusing on blended and online entrepreneurial learning and teaching. Based on five keywords, collating an initial set of 121 articles, this systematic review details the research outcomes of the resulting set of 38 published research articles/contributions, where each described a specific online and blended learning environment. We obtained and analyzed the following information from each of these articles: definition of entrepreneurship education, context of study, methodology, applied technology, focused group, sample, outcome of entrepreneurship education and research rigor. Our findings showed that the current research status and achievements scholars have contributed in educational technologies utilized by online and blended entrepreneurship education can be summarized into three categories: social media, serious games and Massive Open Online Courses. In order to compare these technologies, we selected five examples from three educational technologies and utilized a marking sheet for evaluation and assessment. In general, it was found that Wiki was used to discuss entrepreneurial concepts and that Facebook was the most common social software in entrepreneurship education. In terms of serious games, FLYGBY and SimVenture facilitated the gamification and enjoyment of entrepreneurship activities the most. Finally, as Massive Open Online Courses platform, Coursera offers plenty of/online entrepreneurship education courses. In a nutshell, in online and blended entrepreneurship education, social media was utilized to facilitate cooperation amongst participants; serious games were used to enhance students’ enjoyment and engagement; and Massive Open Online Courses provided a platform as well as high-quality learning resources, anywhere anytime. Hence, each technology has advantages and challenges when we apply it to entrepreneurship education. We conclude that instructors and learners need to successfully compare and choose the most appropriate combination of technologies to achieve entrepreneurial course aims.

. She has published around 30 scientific articles primarily in the area of mobile learning. Source-code plagiarism in universities -A comparative study of student perspectives in China and the UKThere has been much research and discussion relating to variations in plagiaristic activity observed in students from different demographic backgrounds. Differences in behaviour have been noted in many studies although the underlying reasons are still a matter of debate. Existing work focuses mainly on textual plagiarism and most often derives results by studying (small) groups of overseas students studying in a Western context. This study investigates understanding of source-code plagiarism (i.e. plagiarism of computer programs) amongst university students in China. The survey instrument was a Chinese translation of a survey previously administered in English in the UK. This paper reports the results of the exploratory survey conducted in China and compares these results to those from the same survey conducted in the UK. The results show that there is a significant difference in understanding between the respondents from the two surveys, and suggest topics which a future and more comprehensive study may focus on.Keywords: source-code; plagiarism; UK; china IntroductionPlagiarism in the academic community is regarded as malpractice and much work has been conducted on how to detect plagiarism, and how to prevent plagiarism by educating students that it is unacceptable behaviour (Bradley, 2011;Twomey et al., 2009). A large volume of pedagogic material is available on university websites and other websites aimed at instructing students about plagiarism avoidance.Detection tools and services such as Turnitin (submit.ac.uk) are available to assist in the process of detecting plagiarism in student coursework consisting of essays and dissertations.In the computing disciplines, much coursework consists of computer programs, and the source-code for these can be plagiarised in a similar way to the contents of an essay. Tools exist to assist in plagiarism detection, such as MOSS (Bowyer and Hall, 1999), JPlag (Prechelt et al., 2002) and Sherlock (Joy and Luck, 1999), but such tools are relatively immature, since these do not detect plagiarism sources originating from the internet.The incidence of (textual) plagiarism and the motives behind it have often been viewed from a demographic and in particular, cultural, perspective. The IPPHEAE project ("Impact of Policies for Plagiarism in Higher Education Across Europe" -ippheae.eu) is currently comparing and evaluating the policies and procedures for detecting and preventing plagiarism, within the countries of the EU, and it is hoped that the further substantial data collected from both staff and students will shed light on the Greece, noted a number of possible factors. These include proficiency in written English, different expectations relating to the examination process (in some countries, for example, assessment is almost completely by written examination), and differing understan...

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