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Recently, interest in collecting and mining large sets of educational data on student background and performance to conduct research on learning and instruction has developed as an area generally referred to as learning analytics. Higher education leaders are recognising the value of learning analytics for improving not only learning and teaching but also the entire educational arena. However, theoretical concepts and empirical evidence need to be generated within the fast evolving field of learning analytics. In this paper, we introduce a holistic learning analytics framework. Based on this framework, student, learning, and curriculum profiles have been developed which include relevant static and dynamic parameters for facilitating the learning analytics framework. Based on the theoretical model, an empirical study was conducted to empirically validate the parameters included in the student profile. The paper concludes with practical implications and issues for future research.
The purpose of this paper is to analyse data on first-year students’ needs regarding academic support services and reasons for their intention to leave the institution prior to degree completion. On the basis of the findings, a digital badge outline is proposed which could contribute to improved communication of academic requirements in order to help students to better adapt to higher education demands. Digital badges might also serve as an indicator for students’ needing additional academic support services.
Students often enter higher education academically unprepared and with unrealistic perceptions and expectations regarding academic competencies for their studies. However, preparedness and realistic perceptions are important factors for student retention. With regard to a proposed model of five academic competencies(time management, learning skills, technology proficiency, self-monitoring, and research skills), incoming students’ perceptions concerning academic staff support and students’ selfreported confidence at a German university were examined. Using quantitative data, an initial exploratory study was conducted (N = 155), which revealed first-year students’ perceptions of the role of academic staff in supporting their development, especially in
research skills, as well as low self-reported confidence in this competence. Thus, a follow up study (N = 717) was conducted to confirm these findings as well as to provide an indepth understanding of research skills. Understanding students’ perceptions is crucial if higher education institutions are to meet students’ needs and provide adequate support services in the challenging first year. Thus, in order to increase student retention, it is
suggested that universities assist first-year students in developing academic competencies through personalised competence-based programs and with the help of emerging
research fields and educational technologies such as learning analytics and digital badges.
Learning analytics design
(2018)
Instructional designers use learning analytics information to evaluate designs of learning environments, learning materials, and tasks, and adjust difficulty levels, as well as measure the impact of interventions and feedback. Integrating real-time educational data and analysis into the design of learning environments, referred to as learning analytics design (LAD), seems to be a promising approach. Valid pedagogical recommendations may be suggested on the fly as learning analytics methodologies and visualizations evolve and as reliable tools become available and ready for classroom practice. This chapter aims to offer an overview on design and analytics of learning environments before reviewing opportunities of learning analytics design for optimizing learning environments in near real time. Learning analytics (LA) use static and dynamic information about learners and learning environments—assessing, eliciting, and analyzing them—for real-time modeling, prediction, and optimization of learning processes, learning environments, and educational decision-making.
Purpose:
The purpose of this paper is to examine the expectations, perceptions and role understanding of academic staff using a model of academic competencies (i.e. time management, learning skills, technology proficiency, self-monitoring and research skills).
Design/methodology/approach:
Semi-structured interviews were conducted with ten members of academic staff at a German university. Participants’ responses to the open-ended questions were coded inductively, while responses concerning the proposed model of academic competencies were coded deductively using a priori categories.
Findings:
Participating academic staff expected first-year students to be most competent in time management and in learning skills; they perceived students’ technology proficiency to be rather high but their research skills as low. Interviews indicated a mismatch between academic staff expectations and perceptions.
Practical implications:
These findings may enable universities to provide support services for first-year students to help them to adjust to the demands of higher education. They may also serve as a platform to discuss how academic staff can support students to develop the required academic competencies, as well as a broader conversation about higher education pedagogy and competency assessment.
Originality/value:
Little research has investigated the perspectives of academic staff concerning the academic competencies they expect of first-year students. Understanding their perspectives is crucial for improving the quality of institutions; their input into the design of effective support services is essential, as is a constructive dialogue to identify strategies to enhance student retention.
E-Learning Symposium 2014
(2014)
Der Tagungsband zum E-Learning Symposium 2014 an der Universität Potsdam beleuchtet die diversen Zielgruppen und Anwendungsbereiche, die aktuell in der E-Learning-Forschung angesprochen werden. Während im letzten Symposium 2012 der Dozierende mit den unterschiedlichen Möglichkeiten der Studierendenaktivierung und Lehrgestaltung im Fokus der Diskussionen stand, werden in diesem Jahr in einem großen Teil der Beiträge die Studierenden ins Zentrum der Aufmerksamkeit gerückt. Dass nicht nur der Inhalt des Lernmediums für den Lernerfolg eine Rolle spielt, sondern auch dessen Unterhaltungswert und die Freude, die die Lernenden während des Prozesses der Wissensakquise empfinden, zeigt sehr anschaulich die Keynote von Linda Breitlauch zum Thema „Faites vos Jeux“ (Spielen Sie jetzt). Der Beitrag von Zoerner et al. verbindet den Gedanken des spiele-basierten Lernens mit dem nach wie vor aktuellen Thema des mobilen Lernens. Auch in diesem Forschungsbereich spielt die Fokussierung auf den Lernenden eine immer herausragendere Rolle. Einen Schritt weiter in Richtung Individualisierung geht in diesem Zusammenhang der eingeladene Vortrag von Christoph Rensing, der sich mit der Adaptivität von mobilen Lernanwendungen beschäftigt. Mit Hilfe zur Verfügung stehender Kontextinformationen sollen gezielt individuelle Lernprozesse unterstützt werden. Alle Beiträge, die sich auf mobile Applikationen und auf Spiele beziehen, sprechen auch die zwischenmenschliche Komponente am Lernen an. So wird neben der Mobilität insbesondere auch der Austausch von Lernobjekten zwischen Lernenden (vergleiche den Beitrag von Zoerner et al.) sowie die Kooperation zwischen Lernenden (siehe Beitrag von Kallookaran und Robra-Bissantz) diskutiert. Der interpersonelle Kontakt spielt allerdings ebenfalls in den Beiträgen ohne Spiel- oder App-Fokussierung eine Rolle. Tutoren werden beispielsweise zur Moderation von Lernprozessen eingesetzt und Lerngruppen gegründet um das problem-orientierte Lernen stärker in den Mittelpunkt zu rücken (siehe Beitrag von Mach und Dirwelis) bzw. näher am Bedarf der Studierenden zu arbeiten (wie in eingeladenen Vortrag von Tatiana N. Noskova sowie in dem Beitrag von Mach und Dirwelis beschrieben). In der Evaluation wird ebenfalls der Schritt weg von anonymen, akkumulierten statistischen Auswertungen hin zu individualisierten Nutzerprofilen im Bereich des Learning Analytics untersucht (vergleiche dazu den Beitrag von Ifenthaler). Neben der Schwerpunktsetzung auf die Lernenden und deren Mobilität rückt das Thema Transmedialität stärker ins Zentrum der Forschung. Während schon die Keynote mit ihrem Spielefokus darauf anspricht, geht es in weiteren Beiträgen darum Abläufe aus der analogen Welt bestmöglich in der digitalen Welt abzubilden. Lerninhalte, die bisher mittels Bildern und Texten für Lehrende und Lernende zugänglich gemacht wurden, werden nunmehr mit weiteren Medien, insbesondere Videos, angereichert um deren Verständnis zu erhöhen. Dies ist beispielsweise geeignet, um Bewegungsabläufe im Sport (vergleiche dazu den Beitrag von Owassapian und Hensinger) oder musikpraktische Übungen wie Bodyperkussion (beschrieben im Beitrag von Buschmann und Glasemann) zu erlernen Lernendenfokussierung, persönlicher Austausch, Mobilität und Transmedialität sind somit einige der Kernthemen, die Sie in diesem Sammelband erwarten. Auch zeigt die häufige Verknüpfung verschedener dieser Kernthemen, dass keines davon ein Randthema ist, sondern sich die Summe aus allen im E-Learning bündelt und damit eine neue Qualität für Lehre, Studium und Forschung erreicht werden kann.
EMOOCs 2021
(2021)
From June 22 to June 24, 2021, Hasso Plattner Institute, Potsdam, hosted the seventh European MOOC Stakeholder Summit (EMOOCs 2021) together with the eighth ACM Learning@Scale Conference.
Due to the COVID-19 situation, the conference was held fully online.
The boost in digital education worldwide as a result of the pandemic was also one of the main topics of this year’s EMOOCs. All institutions of learning have been forced to transform and redesign their educational methods, moving from traditional models to hybrid or completely online models at scale. The learnings, derived from practical experience and research, have been explored in EMOOCs 2021 in six tracks and additional workshops, covering various aspects of this field. In this publication, we present papers from the conference’s Experience Track, the Policy Track, the Business Track, the International Track, and the Workshops.
Modularization describes the transformation of MOOCs from a comprehensive academic course format into smaller, more manageable learning offerings. It can be seen as one of the prerequisites for the successful implementation of MOOC-based micro-credentials in professional education and training. This short paper reports on the development and application of a modularization framework for Open Online Courses. Using the example of eGov-Campus, a German MOOC provider for the public sector linked to both academia and formal professional development, the structural specifications for modularized MOOC offerings and a methodology for course transformation as well as associated challenges in technology, organization and educational design are outlined. Following on from this, future prospects are discussed under the headings of individualization, certification and integration.