Improving educational practice through reflection is one important focus of teacher professional development approaches. However, such teacher reflection operates under practical classroom constraints that make it happen infrequently, including the reliance on disruptive peer/supervisor observations or recordings. This article describes three design-based research iterations towards technological support for teacher reflection based on everyday evidence and feedback. The authors collaborated with 16 teachers from two different secondary schools, using a variety of prototype technologies (from paper prototypes to web applications and wearable sensors). The iterative evaluation of such prototypes led them from a high-tech focused approach to a more nuanced socio-technical one, based on lightweight technologies and ‘envelope routines’ that also involve students. After illustrating the potential of this approach to change teacher practice and students’ learning experience, the authors also present a series of guidelines for the design of technology that supports such reflection based on everyday evidence gathering.

Research indicates that data-informed practice helps teachers change their teaching and promotes teacher professional development (TPD). Although educational data are often collected from digital spaces, in-action evidence from physical spaces is seldom gathered, providing an incomplete view of the classroom reality. Also, most learning analytics tools focus on learners and do not explicitly collect or analyse teaching data. To support teacher-led inquiries in TPD, the authors’ Design-Based Research explores the feasibility and effects of teachers actively collecting, with the help of technology, data about their classroom practice and the possible impact of such data on their own teaching. Based on an online survey (N = 94), prior research literature and feedback from teachers (N = 11), the authors demonstrate the feasibility of such data collection and suggest design principles for classroom data-collection tools as, besides usability and ease of use, they also detected interest in customisation, triggering teacher interest and inclusion of teaching data.

Purpose: This paper aims to present a teaching approach to achieve the most personal support for students with different backgrounds and preferences in studying an Informatics course. Design/methodology/approach: The presented methodology is based on the main principles of flexible and blended learning. The authors considered three main aspects: student’s background, the level of knowledge and the most suitable style of learning. At the beginning of the course, students were randomly divided into reference and test group. The test group students were continuously supported by different tools within an e-learning environment. The learning process for the reference group students was held in a traditional form. Findings: The success of the experiment presented in this paper is demonstrated by comparing the results of the test group who were taught using the new strategy with the reference group who were taught in a common way. The statistical analysis shows that the test group students had better achievements compared to the reference group. Research Limitations/implications: This presented study was carried out with non-IT first-year university students from social sciences, economics and technical faculties. Each year the number of students varied from 150 to 300. Originality/value: Based on developed methodology, the model of individualization of the educational process in an e-environment was created and implemented in the course of Informatics in Tallinn University of Technology.

The collection of evidence from authentic classroom practice is important both for teacher professional development (TPD) and educational research. However, most current learning analytics (LA) fails to capture the physical occurrences of the classroom, and do not always address individual teachers' needs. More customizable forms of classroom data collection (e.g., through video-recordings or by human observers) are time-consuming and expensive to implement. Navigating this tradeoff between the personalization of data collection and the strict time/effort constraints of classroom practice is still an unsolved challenge for designers of LA and teaching analytics (TA) systems to be used in face-to-face classrooms. In this paper, we extract lessons learnt from a design-based research process that explores this tradeoff, towards the development of teacher-driven, personalizable data collection tools. Through a survey of 15 expert teachers and paper and software prototype testing with a total of 14 teachers in simulated and authentic settings, we gathered information about teachers' preferences for teacher-driven data collection in classrooms, and derived design insights (e.g., a cold-start problem and the need for multiple layers in the personalization), which can be useful for the design of TA/LA tools that collect personalized data from everyday classrooms.

The present article introduces the importance of Scholarship of Teaching and Learning (SoTL) in engineering education and principles of effective teaching and learning in engineering. Examples and experiences of implementing SoTL at Tallinn University of Technology (TUT), Estonia are provided. Principles of SoTL, collegial coaching, continuing education of the faculty, and mentoring are presented in the framework of the main model of Engineering Pedagogy Science. The results of preliminary pilot analysis of levels of evolution of engineering educators at Tallinn University of Technology (TUT) are presented.