Goal of the project

The aim of the project is to structure and process the data generated by students in order to support them in optimizing their learning behavior. This direct feedback to the generated data enables students to better manage their studies. As a consequence, the studyability will be increased (in the sense of personal goal achievement) and the university is perceived more strongly as a supportive place of learning. 

The focus is on evidence-based learning support and intervention in order to adapt learning content and pathways to the needs of students. In addition to the development of online dashboards, the project also provides tutoring and mentoring measures and develops freely available didactic models and guidelines, so that learning coaches can support students better. 

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As addressed in the goals above, the project intends for integrated measures:

  • LA measures at the course level: Development of LA tools such as student and teacher dashboards based on open source technologies for the learning management systems used at the participating universities and making these tools available to other universities. 
  • LA measures in and after the university entry period: Specific measures are taken for this critical study period in order to reduce the number of dropouts and to prepare first-year students as well as possible for the challenges of university learning.
  • Ethical and legal measures related to LA measures: A particular challenge in the use of data relates to data protection and ethical issues.  Based on a legal opinion on data protection law, the project will develop an openly licensed catalog of criteria to ensure compliance with ethical and legal principles. In addition, recommendations for the implementation of the criteria catalog will be formulated. 
  • Since the interpretation of the results and data visualizations in online dashboards is carried out by the students without psychological support, the design of feedback elements conducive to learning is of particular importance in order to be able to strengthen behavior conducive to learning in the students (e.g. self-efficacy, experience of autonomy and competence). In addition to the adherence to international reference models, a validation on the basis of focus groups is planned at different universities. 
  • In addition, the joint interpretation of the processed data will also be incorporated into tutoring and mentoring programs and student counseling
  • A review of the effectiveness of the measures is also planned, as is appropriate preparation for the transfer of information to other Austrian universities.

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Project Schedule

  • 2020-2021: Implementing several prototype courses accompanied by LA measures.  
  • 2020-2022: Developing LA tools such as student and instructor dashboards based on the university-wide learning management systems, including the development of corresponding analysis models
  • 2020-2022: Developing LA measures for the university entry period. 
  • 2020-2022: Developing a catalog of ethical and legal criteria and recommendations for universities
  • 2020-2021: Training students for tutoring or mentoring measures
  • 2020-2022: Developming adaptable didactic models and guidelines and implementing workshops for teachers for feedback to students that is conducive to learning
  • 2020-2021: Establishing a contact point at at least one applicant university, which advises students and teachers on the interpretation of data analyses and visualizations and also makes this know-how available to other stakeholders (such as the student council, the dean(s) of studies or the student advisory service).
  • 2021-2022: Testing the transfer measures for the interpretation of the data analyses and visualizations for students and elaborating corresponding recommendations 
  • 2021-2022: Disseminating the project results for a sustainable implementation of LA measures in the Austrian higher education landscape, e.g. through appropriate publications. 

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Work packages

The measures described result in the following work packages (WP):

  • WP1: Project management: executing project management, organizational support and implementation; writing interim and final reports, financial management.
  • WP2: Developing LA tools such as analysis models, student and instructor dashboards for the university-wide learning management systems based on data and corresponding prototype applications
  • WP3: Developing LA-based measures to improve learning performance in the critical period of university entry, based on the hypothesis: "Learning success in the first year of study is fundamental for further study success"
  • WP4: Developing a set of criteria for the ethical dimension of data analyses and data protection for student data as well as recommendations for universities
  • WP5: Developing measures for feedback conducive to learning: tutoring & mentoring measures, student counseling and workshops for teachers. Development of didactic models and guidelines for the exchange between students and their learning coaches.
  • WP6: Disseminating the results on national (workshops) and international (conferences) level. All results are freely available for further use (analysis models, Moodle plugins, didactic models and guidelines, legal and ethical recommendations).
  • WP 7: Change management supports project management with a holistic view of the change to be undertaken, from the pre-project phase (initiating change) to the planning phase (starting change), the implementation phase (coordinating change), and the project closing (completing change).
  • WP 8: The stabilisation phase is about the sustainable integration of the change in the line organisation, with a special focus on the desired changes in behaviour and attitudes as well as consistency in the adapted processes and procedures. 

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Within the applicant universities, the project should lead to LA activities being established on a pilot basis and being able to be continued accordingly. On the Austrian level, the developed LA measures are to be processed and the Moodle-based LA tools are to be made available on the basis of open source technologies in order to be able to generate the greatest possible benefit.

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Learning Analytics Project-Team: