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Video in education has become pervasive. Globally, educators are recording instructional videos to augment their students' learning and, in many contexts, replace face-to-face lectures. However, the mere act of watching a video is primarily a passive learning experience likely leading to lack of student engagement hindering learning. Active learning strategies such as video annotations and in-video questions have the potential to shift the passive experience of watching an instructional video to a more active one by engaging students with learning strategies designed to promote self-regulated learning and improve content knowledge. This experimental study investigates the impact of in-video questions compared to video annotations on learning and self-efficacy in an experimental setting. Findings revealed that learners who annotated videos had higher self-efficacy than those who completed in-video questions likely due to the immediate feedback received from the in-video questions. The study further concluded that prior knowledge plays a critical role in selecting appropriate active learning strategies, suggesting that video annotations be considered when students have prior knowledge about a topic whereas in-video questions with immediate feedback be interspersed in videos when students do not have prior knowledge about a topic.

The learning analytics community has matured significantly over the past few years as a middle space where technology and pedagogy combine to support learning experiences. To continue to grow and connect these perspectives, research needs to move beyond the level of basic support actions. This means exploring the use of data to prove richer forms of actions, such as personalized feedback, or hybrid approaches where instructors interpret the outputs of algorithms and select an appropriate course of action. This paper proposes the following three contributions to connect data extracted from the learning experience with such personalized student support actions: 1) a student--instructor centred conceptual model connecting a representation of the student information with a basic set of rules created by instructors to deploy Personalized Learning Support Actions (PLSAs); 2) a software architecture based on this model with six categories of functional blocks to deploy the PLSAs; and 3) a description of the implementation of this architecture as an open-source platform to promote the adoption and exploration of this area. Notes for practice include the following: (1) The report draws on research findings related to the effect of personalized feedback on student satisfaction and academic performance (Pardo, Jovanovic, Dawson, Gaševic, & Mirriahi, 2018); (2) The main contribution is the description of the design and implementation of an open source platform for researchers and practitioners to connect data with personalized learning support actions; (3) The area of learning analytics needs tools such as the one described in this document to serve as a vehicle to exchange insights among researchers and practitioners; and (4) This is an example of the note for practice and research.

Digital education, now common in higher education, is particularly evident in the expansion of blended and fully online offerings at universities. Central to this expansion are educational developers, staff who support teaching and learning improvement in courses they do not themselves teach. Working closely with staff, students, and the curriculum, educational developers see first-hand how the digital learning agenda is both implemented and experienced. This article reports on findings from a national study of three educational development groups: academic developers, academic language and learning developers, and online educational designers, from 14 Australian universities. Although their institutional settings, roles, and work practices varied considerably, a central theme was the tension arising from a perceived shift in institutional priorities from 'people development' to 'product development': that is, from building human (educator) capacity towards curriculum resource development, particularly for the online environment. Participants reported a decline in autonomy, with institutional strategy and targeted projects increasingly directing both the work that gets done, and the skill sets required to do it. Their observations have implications for how universities conceptualise the development and support of the educational process.

This paper reports on a subset of findings from a larger study investigating resistance from academic staff to the integration of technology with on-campus foreign language teaching at one North American higher education institution. The study revealed that the factors influencing technology adoption paralleled Davis' Technology Acceptance Model's tenets of perceived usefulness and ease of use. Further, this study supports Lai and Savage's (2013) assertion of a lack of attention to the pedagogical affordances of technology when adoption decisions are made by instructors, thus we highlight the need for higher education leaders to determine strategies promoting awareness of the benefits technology-enabled teaching and learning can bring to advance educationally-rich flexible learning opportunities.

This study built on previous research in 2010 to determine changes to students' current use of and expectations for future integration of technologies in their learning experience. The findings reveal a continued trend of conservative technology use amongst students but with a growing demand for more integration of technologies for assessment and administrative purposes, podcasts or lecture recordings in flexible and blended course designs. While academic practice has been slow to change, this study reveals a continued need for academic development to focus on strategies that enhance technology adoption amongst academic staff. Students' preferences from this and the earlier study suggest that they would like more use of technologies, especially mobile technologies for efficient and convenient access to content, communication and assessment that can not only inform academic development and course design for fully online and blended learning courses, but also for the growing number of massive open and online courses (MOOCs) in the education landscape.

This paper reports on the current experience of one higher education institution in Australia embarking on the path towards mainstreaming online learning opportunities by providing three complementary academic development initiatives that can inform strategies undertaken by other institutions internationally. First, an academic development program was redesigned and delivered in blended mode to provide teaching staff with the experience of learning in a blended environment to raise their awareness of effective strategies. Second, an accredited postgraduate course for teaching staff on the subject of educational design was redesigned to focus on strategies for online and blended course design and delivered fully online to raise awareness of online learning benefits. Third, a Massive Open Online Course (MOOC), entitled Learning to Teach Online (LTTO), was developed to offer professional development opportunities to teaching staff at the higher education institution, as well as to a wider international audience of educators. The threefold professional development strategies reported in this paper provide teaching staff with an opportunity to interact, mentor, and share knowledge with one another, alongside experiencing online and blended learning to effectively meet the challenge of improving the digital literacy of teaching staff and enhancing effective online and blended learning opportunities for students.

Designing, validating, and deploying learning analytics tools for instructors or students is a challenge that requires techniques and methods from different disciplines, such as software engineering, human-computer interaction, computer graphics, educational design, and psychology. Whilst each has established its own design methodologies, we now need frameworks that meet the specific demands of the cross-disciplinary space defined by learning analytics are needed. In particular, LAK [Learning Analytics and Knowledge] needs a systematic workflow for creating tools that truly underpin the learning experience. In this paper, we present a set of guiding principles and recommendations derived from the LATUX workflow. This is a five-stage workflow to design, validate, and deploy awareness interfaces in technology-enabled learning environment. LATUX is based on well-established design processes for creating, testing, and re-designing user interfaces. We extend existing approaches by integrating the pedagogical requirements needed to guide the design of learning analytics visualizations that can inform pedagogical decisions or intervention strategies. We illustrate LATUX in a case study of a classroom with collaborative activities. Finally, the paper proposes a research agenda to support designers and implementers of learning analytics interfaces.

The success of the flipped classroom (FC) is effectively reliant on the level of student engagement with the preparatory activities prior to attending face-to-face teaching sessions. Information about the nature and level of student engagement with these activities can help instructors make informed decisions regarding how to best support student learning. Despite the comprehensive data collection enabled by the increasing presence of education technologies, few studies have used these data to investigate the range of strategies students employ in FC models. This study addresses this deficit by proposing an analytical approach that allows for exploring, first, the strategies students use to interact with online preparation activities; and, second, evolution of those strategies over the duration of a course delivered with a FC pedagogy. The proposed approach identified eight learning strategies and six trajectories of strategy change over the duration of the course, with statistically significant effects of strategy change trajectories on academic performance.

There is little debate regarding the importance of student feedback for improving the learning process. However, there remain significant workload barriers for instructors that impede their capacity to provide timely and meaningful feedback. The increasing role technology is playing in the education space may provide novel solutions to this impediment. As students interact with the various learning technologies in their course of study, they create digital traces that can be captured and analysed. These digital traces form the new kind of data that are frequently used in learning analytics to develop actionable recommendations that can support student learning. This paper explores the use of such analytics to address the challenges impeding the capacity of instructors to provide personalised feedback at scale. The case study reported in the paper showed how the approach was associated with a positive impact on student perception of feedback quality and on academic achievement. The study was conducted with first year undergraduate engineering students enrolled in a computer systems course with a blended learning design across three consecutive years (N[subscript 2013] = 290, N[subscript 2014] = 316 and N[subscript 2015] = 415).

The use of standards-based assessment (SBA) has gained prominence in higher education due to a wide range of research evidence that supports its effectiveness in improving learning and teaching. Although the concept is widely used in academic discourse and practice, it has multiple interpretations which have led to diverse assessment practices to the extent that some of these depart from the principles of SBA. To help build a common understanding of what constitutes SBA practices, we explored the construct of academic SBA practices using both theoretical and empirical approaches. We developed a tool, based on the principles of SBA emerging from practices noted in the literature and identified from focus groups. We used factor analysis to extract the dimensions of the construct and to establish empirical evidence for the utilisation of the tool using a data set of 410 academics who engaged in self-assessment. Results showed that a six-factor model is the most parsimonious among other models. We used these dimensions to develop a framework for describing academic SBA practices. The use of the framework and tool has critical implications for curriculum design, professional practice and development, and policy articulation.

This article reports on the findings of a study that investigated the effects of instructional conditions and prior experience on students' self-reflection. The study was conducted with the use of a video annotation tool that was used by undergraduate performing arts students to reflect on their video-recorded performances. The study shows a consistent positive effect of previous experience with the video annotation tool for engagement with reflection. Graded instructional conditions with feedback had a positive effect on increasing higher order reflections particularly for students with prior experience with the video annotation tool for reflective purposes. The finding suggests that when including reflection in the curriculum, it is important to consider introducing it at a program or degree level rather than individual courses in order to provide an opportunity for students to gain experience with reflection and any particular tool that is used (e.g., a video annotation tool). Furthermore, reflective tasks should be scaffolded into the curriculum with ample opportunity for formative feedback and summative assessment in order to encourage higher order thinking and foster students' metacognitive awareness and monitoring for increased goal-setting and acknowledgement of the motive or effect of their observed behavior.

The rapid growth of blended and online learning models in higher education has resulted in a parallel increase in the use of audio-visual resources among students and teachers. Despite the heavy adoption of video resources, there have been few studies investigating their effect on learning processes and even less so in the context of academic development. This paper uses learning analytic techniques to examine how academic teaching staff engage with a set of prescribed videos and video annotations in a professional development course. The data was collected from two offerings of the course at a large research-intensive university in Australia. The data was used to identify patterns of activity and transition states as users engaged with the course videos and video annotations. Latent class analysis and hidden Markov models were used to characterise the evolution of engagement throughout the course. The results provide a detailed description of the evolution of learner engagement that can be readily translated into action aimed at increasing the quality of the learning experience.

This study explores the types of learning profiles that evolve from student use of video annotation software for reflective learning. The data traces from student use of the software were analysed across four undergraduate courses with differing instructional conditions. That is, the use of graded or non-graded self-reflective annotations. Using hierarchical cluster analysis, four profiles of students emerged: minimalists, task-oriented, disenchanted, and intensive users. Students enrolled in one of the courses where grading of the video annotation software was present, were exposed to either another graded course (annotations graded) or non-graded course (annotations not graded) in their following semester of study. Further analysis revealed that in the presence of external factors (i.e., grading), more students fell within the task-oriented and intensive clusters. However, when the external factor is removed, most students exhibited the disenchanted and minimalist learning behaviors. The findings provide insight into how students engage with the different features of a video annotation tool when there are graded or non-graded annotations and, most importantly, that having experience with one course where there are external factors influencing students' use of the tool is not sufficient to sustain their learning behaviour in subsequent courses where the external factor is removed.

The need for flexibility in learning and the affordances of technology provided the impetus for the rise of blended learning (BL) globally across higher education institutions. However, the adoption of BL practices continues at a low pace due to academics' low digital fluency, various views and BL definitions, and limited standards-based tools to guide academic practice. To address these issues, this paper introduces a BL framework, based on one definition and with criteria and standards of practice to support the evaluation and advancement of BL in higher education. The framework is theoretically underpinned by the extant literature and supported by focus group discussions. The evidence supporting the criteria and standards are discussed with suggestions for how they can be used to guide course design, academic practice, and professional development.

Digital education, now common in higher education, is particularly evident in the expansion of blended and fully online offerings at universities. Central to this expansion are educational developers, staff who support teaching and learning improvement in courses they do not themselves teach. Working closely with staff, students, and the curriculum, educational developers see first-hand how the digital learning agenda is both implemented and experienced. This article reports on findings from a national study of three educational development groups: academic developers, academic language and learning developers, and online educational designers, from 14 Australian universities. Although their institutional settings, roles, and work practices varied considerably, a central theme was the tension arising from a perceived shift in institutional priorities from 'people development' to 'product development': that is, from building human (educator) capacity towards curriculum resource development, particularly for the online environment. Participants reported a decline in autonomy, with institutional strategy and targeted projects increasingly directing both the work that gets done, and the skill sets required to do it. Their observations have implications for how universities conceptualise the development and support of the educational process. [ABSTRACT FROM AUTHOR]

Mind wandering is a common experience for students. About 30% of the time, while learning, they will think about something unrelated, such as what they have planned for dinner. These off-task thoughts negatively impact their learning outcomes (Wong et al., 2022). Previous research has been conducted in video-based learning to assert whether including interpolated testing at pauses in a video leads to reduced mind wandering and improved learning outcomes (Jing et al., 2016; Szpunar et al., 2013; Welhaf et al., 2022). The results of these studies have been mixed and do not clearly show that interpolated testing at pauses in a video has the desired effect. Therefore, it has been suggested that interpolated testing only has limited practical effect on reducing mind wandering (Welhaf et al., 2022). In this study, we aim to determine if writing self-explanations at pauses in a video has a stronger effect on reducing mind wandering and increasing learning outcomes than interpolated testing. For this study, we recruited 138 participants, distributed across three groups. The participants were asked to watch the same video called "Why is blue so rare in nature?" across all three groups (see https://youtu.be/3g246c6Bv58). The difference between the three groups was in the interaction the participants were asked to engage in at pauses in the video. The pause times were identical across groups. The first group, the control group (n = 47), was only asked about their thoughts. The second group, the interpolated testing group (n = 51), answered multiple-choice questions. The third group, the self-explanation group (n = 40), was asked to write an explanation to themselves about what they learned. Knowledge gain was measured using a knowledge test before and after the video. Additionally, all participants were instructed to monitor their thoughts and click on a button whenever they realized they were mind wandering. This way of measuring mind wandering deviates from previous studies investigating mind wandering while learning from video. In previous research, mind wandering was measured using probe-caught thought reports. When using this method, the participants are interrupted periodically and instructed to report whether they were mind wandering. We deviate from this measurement method because we expect, based on generative learning theory (Fiorella & Mayer, 2015), that the expectation of having to write a self-explanation will lead the participants to be more aware of their thoughts. To test this hypothesis, we used self-caught thought reports and asked the participants to selfreport their mind wandering once they realized they were mind wandering. The results of our analysis using a Kruskal-Wallis test show no significant difference between the groups in their knowledge gain (H(2) = 1.9, p = .38) or the number of thought reports written (H(2) = 3.45, p = .18). However, the number of thought reports written correlates with knowledge gain (τ = .15, H(1) = 2.33, p = .01). This result indicates that participants who were more aware of their mind wandering performed better on a knowledge test after the video. While it is inevitable that mind wandering will occur, the deciding factor on whether this mind wandering negatively influences the learning outcomes could be how aware the students are of their thoughts while learning. Consequently, further research should be conducted into how this awareness of mind wandering can be increased. [ABSTRACT FROM AUTHOR]