Research Projects by Prof. Dr. Sascha Schanze

  • Peer-Interaction-Methode (PIM)
    Promoting conceptual understanding through a collaborative task format: The Peer Interaction Method (PIM) is a two-phase collaborative learning form guided by work sheets to promote understanding of general chemical concepts. The research focus is on conditions for success in order to derive suitable instructions or recommendations for an adequate group composition.
    Led by: Prof. Dr. Sascha Schanze
    Team: Julian Heeg, Dr. Sarah Hundertmark
    Year: 2016
  • digiPro - Improving understanding Chemistry by using a digital problem-based learning environment
    digiPro provides both students and lecturers of chemistry-specific degree programmes with a practice-based digital learning environment based on the learning management system ILIAS. The research focus is on the design of suitable sample tasks (explanatory videos) or (collaborative) learning tasks to promote problem solving and representational competence.
    Led by: Prof. Dr. Sascha Schanze
    Team: Dennis Zehler
    Year: 2019
    Funding: MWK- Programms "Qualität plus-Programm zur Entwicklung des Studiums von morgen"
    Duration: 01/2019-12/2021
  • Leibniz Prinzip II – field of action 2: Modern Formats of Learning - digital, reflective, didactically structured/teaching methodology structured
    High-quality teaching focuses on the individual learning requirements of students and integrates digitally supported elements. The aim of this field of action is to promote digital competences for the reflection and design of student-oriented learning spaces among prospective teachers. To this end, teaching and learning spaces appropriate for the target group are digitally designed and supported in the university phase of teacher training.
    Led by: Prof. Dr. Sascha Schanze
    Team: Robert von der Heide
    Year: 2019
    Funding: BMBF
    Duration: 2019-2024
  • LernMINT - Data-driven teaching in STEM subjects.
    Digital Transformation offers a variety of opportunities for school and university education. Although the integration of digital technologies in mathematics and science education as a teaching and learning tool already has a long tradition, there is a lack of studies, especially in STEM subjects, that embed data-driven learning analytics methods in STEM education concepts, evaluate their educational opportunities and limitations, and at the same time consider the aspects of data protection and fairness.
    Led by: Prof. Dr. Ralph Ewerth, Prof. Dr. Gunnar Friege
    Team: Prof. Dr. Andreas Nehring, Prof. Dr. Sascha Schanze, Prof. Dr. Reinhard Hochmuth, Prof. Dr. Johannes Krugel, Dr. Anett Hoppe, Prof. Dr. Eirini Ntoutsi, Prof. Dr. Sarah Dannemann, Prof. Dr. Christian Wartena, Prof. Dr. Katrin Thiele
    Year: 2020
    Funding: Niedersächsisches Ministerium für Wissenschaft und Kultur
    Duration: 2020-2024