Combining concept maps and interviews to produce representations of personal professional theories in higher vocational education: effects of order and vocational domain

This article is about the use of personal professional theories (PPTs) in Dutch higher vocational education. PPTs are internalised bodies of formal and practical knowledge and convictions, professionals use to direct their behaviour. With the aid of high-quality representations of students’ PPTs teachers can access, monitor, and support the professional development of students. Two qualitatively equivalent techniques for representing PPTs are (computer-supported) concept mapping and interviewing. This article reports on a study of the effects of combining these techniques to determine whether (1) this results in higher quality representations and (2), if so, whether technique order will make a difference. The study was conducted in two very different vocational domains: accountancy with 29 participants and teacher education with 20 participants. The results of a counterbalanced quasi-experiment with two factors (i.e. domain and order) show in both domains that combining the techniques improves quality but order does not matter. This order independence has practical importance as the computer-supported analysis of a student generated concept map and subsequently discussing the results with the student, fosters learning and fits in educational practice well

Facilitating reflection: a review and synthesis of the factors enabling effective facilitation of reflective practice

© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Reflective practice is an inherently personal and relational process, occurring privately within people, and publicly, between people. Consequently, given it positively impacts on professional practice, it has become a personal and professional requirement for professional bodies accrediting practitioners. This literature synthesis aims to consolidate understanding around the factors facilitating reflection by generating insights from a variety of publications across professional contexts. The analytical process involved initial coding and focussed coding wherein article text was fragmented, sorted, and integrated to develop a thematic structure. Analysis resulted in two higher order themes: Factors facilitating reflection; and Facilitator tasks. Results highlighted the value of supportive environments to facilitate open enquiry alongside focussed formal dialogues between peers, more experienced colleagues, and formal facilitators to enrich knowledge, perspectives, insights, and relationships. Further, to begin the reflective process, practitioners and novice learners benefit from support in deconstructing the concept of reflection. Ideally, this would be facilitated by an experienced reflective facilitator who values an open enquiry towards complexity, difference, and emotive responses. This requires safe, supportive, and blame-free environments where facilitators encourage dialogue while modelling qualities such as congruence, acceptance, and empathy.Peer reviewe

Knowledge discovery through creating formal contexts

Knowledge discovery is important for systems that have computational intelligence in helping them learn and adapt to changing environments. By representing, in a formal way, the context in which an intelligent system operates, it is possible to discover knowledge through an emerging data technology called formal concept analysis (FCA). This paper describes a tool called FcaBedrock that converts data into formal contexts for FCA. This paper describes how, through a process of guided automation, data preparation techniques such as attribute exclusion and value restriction allow data to be interpreted to meet the requirements of the analysis. Examples are given of how formal contexts can be created using FcaBedrock and then analysed for knowledge discovery, using real datasets. Creating formal contexts using FcaBedrock is shown to be straightforward and versatile. Large datasets are easily converted into a standard FCA format