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The purpose of this chapter is to explore whether undertaking a scaffolded form of classroom-based research could support postgraduate university– school initial teacher education partnership programmes. Our design for supporting student teachers to execute a Close-to-Practice (CtP) based empirical study is described including methodological and philosophical underpinnings. Close-to-practice (CtP) research is defined as research that ‘focusses on defined by practitioners as relevant to their practice, and involves collaboration between people whose main expertise is research, practice, or both.’ (BERA, 2018). In the case of this study, issues were decided in collaboration between student teachers and schools. In terms of evaluation of the efficacy of such an approach, a qualitative methodology was undertaken, comprising of a critical discourse analysis of student teacher written research reports. Discourse analysis revealed that several sociocognitive processes took place during, and as a result of, student teachers engaging in CtP research, including explorations of identity, polarisation to collective groups, articulation and examination of beliefs and values and negotiation of existing power relationships and structures. In addition, the data showed that many aspects of undertaking a small-scale research study supported student teacher pedagogical knowledge acquisition and professional development. Student teacher testimony also revealed they valued this mode of learning and developed positive attitudes to educational research in the widest sense. This study has clear implications for the design of initial teacher education programs and the continued professional development of teachers, in England and potentially further afield.

Copyright © 2019: Sarah Dart, Kim Blackmore, Keith Willey, Anne Gardner, Smitha Jose, Raj Sharma, Sloan Trad, Lesley Jolly:. Many engineering academics interested in quality teaching and learning dabble with educational research. Some go further leaving their technical research field behind to embark head-long into what for many is an initially bewildering and conceptually challenging domain. Often peers perceive this transition as a crime (giving up on real engineering) liable to be punished with reduced access to funding and institutional recognition for one's research. The Australasian Association for Engineering Education (AAEE) has been sponsoring a Winter School in Engineering Education Research Methods since 2011, to help engineering academics change their transition story from one of crime and punishment to success and reward. While helpful, this transition is not a simple matter of learning new techniques but of altering one's perspective and habits of thinking and behaviour. Many participants find this both challenging and at least initially, a lonely pursuit. In this paper, participants in the 2018 school ask the question "what enables and hinders the transition to educational research".

The rapid changes occurring in the higher education domain are placing increasing pressure on the actors in this space to focus efforts on identifying and adopting strategies for success. One particular group of interest are academics or scientists, and the ways that these individuals, or collectives as institutional or discipline-based science systems, make decisions about how best to achieve success in their chosen field. The agent-based model and simulation that we present draws on the hypothetical “strategic publication model†proposed by Mölders, Fink and Weyer (2011), and extends this work by defining experimental settings to implement a prototype ABMS in NetLogo. While considerable work remains to fully resolve theoretical issues relating to the scope, calibration and validation of the model, this work goes some way toward resolving some of the details associated with defining appropriate experimental settings. Also presented are the results of four experiments that focus on exploring the emergent effects of the system that result from varying the strategic mix of actors in the system.

© 2014 ACM. Understanding player experiences is central to game design. Video captures of players is a common practice for obtaining rich reviewable data for analysing these experiences. However, not enough has been done in investigating ways of preprocessing the video for a more efficient analysis process. This paper consolidates and extends prior work on validating the feasibility of using automated facial expressions analysis as a natural quantitative method for evaluating player experiences. A study was performed on participants playing a first-person puzzle shooter game (Portal 2) and a social drawing trivia game (Draw My Thing), and results were shown to exhibit rich details for inferring player experiences from facial expressions. Significant correlations were also observed between facial expression intensities and self reports from the Game Experience Questionnaire. In particular, the challenge dimension consistently showed positive correlations with anger and joy. This paper eventually presents a case for increasing the application of computer vision in video analyses of gameplay.