QHelp

Higher Education Learning Platform for Quantitative Thinking

01.09.2019 bis 31.12.2022

Understanding of, critically reflecting on and communicating of statistical information and quantitative concepts has become a fundamental skill and competence for an informed and active citizen in a modern society.
There is a worrying trend, particularly in the social sciences, that requires urgent attention. An increasing number of results reported in the literature and media are not replicated, misleading or plain wrong. The underlying problem seems to be inaccurate or inappropriate use of quantitative methods and thinking.

Ideally, teaching quantitative thinking would be based on interactive activities supervised by several experts so that a student continuously receives personalized feedback. If however teaching is delivered face-to-face or in a traditional classroom format, then this would be very costly and timeconsuming. We need adaptive and personalized learning tools, available online to a large and diverse group of students. Such tools would promote quantitative reasoning, reflection and communication. It is planned to develop the e-learning system QHelp that allows both adaptive assessment of competencies and skills, and personalized learning. The QHelp platform will merge into a single integrated e-learning platform two important types of tools for e-learning: the massive open online courses (MOOC) and the intelligent tutoring system (ITS).

The QHelp project is both innovative and complementary to the TquanT project carried out from 2015 to 2018 within the EU Erasmus+ programme. The QHelp system will be composed of two fundamental modules: an assessment and a learning module. The former will be used for determining
the state of knowledge of a student. This will be done by applying the adaptive assessment procedures that are available in the knowledge space theory (KST) framework. At the end of the assessment the student will receive a detailed report containing the results of the assessment in both summative and formative terms. In the learning module the student will be guided through the contents in a structured way, starting from the notions, knowledge and concepts that are immediately accessible from her state of knowledge. This personalized learning should help keeping high the student’s motivation to stay in the system.