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This paper outlines an innovative approach to evaluating the emotional content of three online courses using the affective computing approach of prosody detection on two different text-to-speech (TTS) voices in conjunction with human raters judging the emotional content of the text. This work intends to establish the potential variation on the emotional delivery of online educational resources through the use of a synthetic voice, which automatically articulates text into audio. Preliminary results from this pilot research suggest that about one out of every three sentences (35%) in a Massive Open Online Course (MOOC) contained emotional text and two existing assistive technology voices had poor emotional alignment when reading this text. Synthetic voices were more likely to be overly negative when considering their expression as compared to the emotional content of the text they are reading, which was most frequently neutral. We also analysed a synthetic voice for which we configured the emotional expression to align with course text, which showed promising improvements.

Teacher Moments is an open source resource for teacher educators to create and use practice-based simulations in teacher education. Teacher Moments may be used to create digital clinical simulations (DCS) which are defined as opportunities for improvisational interaction with scripted character(s). During the COVID-19 crisis, we implemented an equity-based simulation created by a teacher educator. Results demonstrate the utility of the system for surfacing student perspectives which, in turn, provides opportunities for deeper discussion and reflection.

Personalisation of learning is a recurring trend in our society, referred to in government speeches, popular media, conference and research papers and technological innovations. This latter aspect--of using personalisation in technology-enhanced learning (TEL)--has promised much but has not always lived up to the claims made. Personalisation is often perceived to be a positive phenomenon, but it is often difficult to know how to implement it effectively within educational technology. In order to address this problem, we propose a framework for the analysis and creation of personalised TEL. This article outlines and explains this framework with examples from a series of case studies. The framework serves as a valuable resource in order to change or consolidate existing practice and suggests design guidelines for effective implementations of future personalised TEL.

Technology makes possible abundant new opportunities to capture and display data in online learning environments. We describe here an example of using these opportunities to improve students' use of the rich supports available in online learning environments. We describe an example of a blended learning experience that uses an online inquiry-based middle-school science curriculum in which we provided sixth graders (n?=?126) data aligned with the Universal Design for Learning instructional framework. Students were provided and asked to reflect on their own data not only about performance but also about use of optional embedded supports vis-à-vis their perceptions of difficulty of key concepts. We determined that students were generally able to understand and interpret these rich data and that providing these data influenced subsequent help seeking in the online environment. We discuss implications for supporting help seeking and designing assessment and feedback within online learning environments.