Toward Emotionally Accessible Massive Open Online Courses (MOOCs)

This paper outlines an approach to evaluating the emotional content of three Massive Open Online Courses (MOOCs) using the affective computing approach of prosody detection on two different text-to-speech voices in conjunction with human raters judging the emotional content of course text. The intent of this work is to establish the potential variation on the emotional delivery of MOOC material through synthetic voice

Understanding Emotions in Online Learning: Using Emotional Design and Emotional Measurement to Unpack Complex Emotions During Collaborative Learning

Many educational researchers explore the role of emotion in learning and there are many new affordances for emotional measurement. Just as there are many options for emotional measurement there are many theories of emotion. When it comes to the measure of sentiment analysis recent findings suggest it is beneficial to online and blended learning research. The sentiment analysis technologies used for educational research are general purpose technologies suggesting that creating a measure designed for the context of learning would improve the alignment between the measure and context. In addition to aligning measure with the context, there is a need to consider how sentiment analysis relates to emotion theory to determine an appropriate method to evaluate the accuracy of sentiment analysis. In this PhD thesis I adopt the Constructed Theory of Emotion, which considers emotion as a collective intentionality indicating that consensus on emotion is the best approach toward examining accuracy. From this perspective I create a sentiment analysis measure in the context of learning to contribute to emotional learning analytics the emerging sub-field of learning analytics. The field of learning analytics acknowledges that design and measurement are intertwined. I adopt a design-based research approach by designing supports for emotional communication and examining how such a design impacts the accuracy of sentiment analysis. I then examine correlation analysis with other established measures of emotion. The results contribute to the field of emotional learning analytics by: • demonstrating promise for generating a classifier based on student perception • demonstrating benefits of supporting emotion expression in text for students • demonstrating that students’ emotion expression in text does not appear to align with their internal emotional experiences These findings provide opportunities for further research and suggest caution should be used when interpreting sentiment analysis results in the context of learning

[Editorial] Special Collection on Doctoral Research: Learning in an Open World

This editorial introduces the JIME special collection focused on “Doctoral Research: Learning in an Open World

Applying UDL Principles in an Inclusive Design Project Based on MOOCs Reviews

The wide-scale adoption of Massive Open Online Courses (MOOCs) comes with learners that have variable needs. While MOOCs may be attracting a wide range of learners, there is a need to provide those learners with a means to evaluate what is working in MOOCs and what areas of learning design can be improved. While learners may have compliments and criticisms of course designs, there is a need to organize feedback from such a wide range of participants into a coherent and actionable structure. This chapter describes the YourMOOC4all project, which offers the possibility for any learner to freely judge and provide feedback on the design of MOOCs in accordance with how it meets learner needs and Universal Design for Learning (UDL) principles. This kind of user feedback can be of great value for the future development of MOOC platforms, courses, and associated educational resources. YourMOOC4all gathers valuable information directly from the learners themselves to improve aspects such as the educational quality, accessibility, and usability of the learning environment

Humanising Text-to-Speech Through Emotional Expression in Online Courses

This paper outlines an innovative approach to evaluate 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 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 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 analyzed a synthetic voice for which we configured the emotional expression to align with course text, which showed promising improvements

Prototyping Visual Learning Analytics Guided by an Educational Theory Informed Goal

Prototype work can support the creation of data visualizations throughout the research and development process through paper prototypes with sketching, designed prototypes with graphic design tools, and functional prototypes to explore how the implementation will work. One challenging aspect of data visualization work is coordinating the expertise of people from a variety of roles to produce data visualizations guided by an educational theory informed goal (ETIG) in order to better support research. When collaborating, concessions must be made: typically, everyone seeks to follow the best practices established within their own disciplines. This paper attempts to illustrate how to rethink this interdisciplinary approach to adhere more strictly to educational research goals and consider how we may need to, at times, break away from best practices with the intent to evaluate the novel decisions resulting from this approach. A case study of the creation of a self-reported emotional measure is used to illustrate this type of collaboration. By taking this approach, a clear departure from best practices occurs in the scale selection for the visualization in order to support the ETIG

A Case Study to Explore a UDL Evaluation Framework Based on MOOCs

In this paper, we focus on 23 undergraduate students’ application of a universal design for learning (UDL) evaluation framework for assessing a massive open online course (MOOC) in the context of a usability and accessibility university course. Using a mixed-methods approach, we first report the extent to which untrained raters agree when evaluating their course with the framework and then examine their feedback on using UDL for assessment purposes. Our results indicate user feedback provides great value for both the future development of accessible MOOCs and identifies opportunities to improve the evaluation framework. For that purpose, we suggest an iterative process comprised of refining the framework while working with students and which could help students to internalise UDL principles and guidelines to become expert learners and evaluators. The complexities and redundancies that surfaced in our research, as reported in this paper, illustrate that there is variability in the perception of both the course design and the interpretation of the framework. Results indicate that UDL cannot be applied as a list of simple checkpoints, but also provide insights into aspects of the framework that can be improved to make the framework itself more accessible to students

The influence of internationalised versus local content on online intercultural collaboration in groups: A randomised control trial study in a statistics course

Computer-supported collaborative learning (CSCL) has been highlighted as a beneficial learning experience for students in blended and online settings. In highly diverse and international contexts, CSCL also allows students the opportunity to encounter new ideas and values from peers with different backgrounds. However, previous research has highlighted that there are wide variations in student participation levels in CSCL activities and that many students experience social and cultural tensions when working with diverse peers. These issues may damage the quality of online collaboration and limit the potential gains of CSCL. In this study, we explored one evidence-based solution for encouraging CSCL participation: the internationalisation of the online academic content used for collaborative activities. Using a randomised control trial method with 428 undergraduate students in an introductory statistics course, we compared individual and group-level participation in an online collaborative task when students used content from the local context compared to content from international contexts. Our findings suggest that internationalisation of online content can encourage individual-level participation and decrease the disparity of participation within small groups when the content is situated in countries that are personally relevant to students’ own backgrounds. At the same time, participation was influenced by individual demographics and group dynamics

Research Evidence on the Use of Learning Analytics: Implications for Education Policy

The evidence shows that the use of learning analytics to improve and to innovate learning and teaching in Europe is still in its infancy. The high expectations have not yet been realised. Though early adopters are already taking a lead in research and development, the evidence on practice and successful implementation is still scarce. Furthermore, though the work across Europe on learning analytics is promising, it is currently fragmented. This underlines the need for a careful build-up of research and experimentation, with both practice and policies that have a unified European vision. Therefore, the study suggests that work is needed to make links between learning analytics, the beliefs and values that underpin this field, and European priority areas for education and training 2020. As a way of guiding the discussion about further development in this area, the Action List for Learning Analytics is proposed. The Action List for Learning Analytics focuses on seven areas of activity. It outlines a set of actions for educators, researchers, developers and policymakers in which learning analytics are used to drive work in Europe’s priority areas for education and training. Strategic work should take place to ensure that each area is covered, that there is no duplication of effort, that teams are working on all actions and that their work proceeds in parallel. Policy leadership and governance practices •Develop common visions of learning analytics that address strategic objectives and priorities •Develop a roadmap for learning analytics within Europe •Align learning analytics work with different sectors of education •Develop frameworks that enable the development of analytics •Assign responsibility for the development of learning analytics within Europe •Continuously work on reaching common understanding and developing new priorities Institutional leadership and governance practices •Create organisational structures to support the use of learning analytics and help educational leaders to implement these changes •Develop practices that are appropriate to different contexts •Develop and employ ethical standards, including data protection Collaboration and networking •Identify and build on work in related areas and other countries •Engage stakeholders throughout the process to create learning analytics that have useful features •Support collaboration with commercial organisations Teaching and learning practices •Develop learning analytics that makes good use of pedagogy •Align analytics with assessment practices Quality assessment and assurance practices •Develop a robust quality assurance process to ensure the validity and reliability of tools •Develop evaluation checklists for learning analytics tools Capacity building •Identify the skills required in different areas •Train and support researchers and developers to work in this field •Train and support educators to use analytics to support achievement Infrastructure •Develop technologies that enable development of analytics •Adapt and employ interoperability standard

UDL and its implications in MOOC accessibility evaluation

Assessing the accessibility of online educational environments is not easy. As we scale up educational technology, like with Massive Open Online Courses (MOOCs), we amplify the impact of (in)accessible designs. With MOOCs, we reach more learners and need to consider the variability that comes with scale. While the challenges and opportunities online learning at scale faces in terms of accessibility are great, the support from educators and technical experts of the platforms that host such courses has historically been minimal. To investigate the current state of accessibility in online educational environment, such as MOOCs, this chapter reports on the development of a learning design evaluation checklist where Universal Design for Learning (UDL) has been adapted. After adapting design guidelines to an evaluation checklist, inter-rater reliability agreement protocols were used to improve and validate the checklist where two raters achieved a Cohen’s Kappa that ranged between 0.55 and 0.59 for three courses. This chapter details the reflective process followed to update the UDL framework, designed for developing accessible educational resources, to an evaluation checklist for MOOCs and the implications this process has for creating expert learners who are expert evaluators