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 (Galek et al., 2012; Boekel, et al., 2014; Leek, McShane, Gelman, Colquhoun, Nuijten, Goodman, 2017; McNut, 2014; Open Science Collaboration, 2015). The underlying problem seems to be inaccurate or inappropriate use of quantitative methods and thinking. If this trend remains unchecked, valuable research money will be wasted and the reputation of of entire research programmes in the social sciences (Kahnemann, 2012) and in other disciplines (Ioannides, 2005, 2014) may be destroyed.
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 time-consuming.
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 2016 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.
The project will produce several outputs that can be distinguished into intellectual outputs, multiplier events, and blended mobility activities. Intellectual outputs will be applications developed with the pedagogical aim of teaching methods and procedures for quantitative data analysis.
Two multiplier events will take place at international conferences and meetings of well-known societies, the Psychometric Society, and at higher education methodological winter schools.
Three blended mobility activities will be held in Tübingen, Leuven, and Padua. These activities will involve students, teachers and researchers from partner universities, and will employ innovative learning and teaching methods. They are essential milestones for achieving the objectives of this project and will lead to the development of new teaching material, software tools, exercises that will be included in the QHelp e-learning system. The activities will provide added value by collecting quantitative and qualitative feedback from participants, and an opportunity for teachers and students to meet, and work on intellectual outputs. The physical mobility will also be used to hold transnational project meetings, to exercise quality control and to identify potential problems at each stage of the project.