Internet and Higher Education最新文献

Unequal stakeholder engagement is a common pitfall of adoption approaches of learning analytics in higher education leading to lower buy-in and flawed tools that fail to meet the needs of their target groups. With each design decision, we make assumptions on how learners will make sense of the visualisations, but we know very little about how students make sense of dashboard and which aspects influence their sense-making. We investigated how learner goals and self-regulated learning (SRL) skills influence dashboard sense-making following a mixed-methods research methodology: a qualitative pre-study followed-up with an extensive quantitative study with 247 university students. We uncovered three latent variables for sense-making: transparency of design, reference frames and support for action. SRL skills are predictors for how relevant students find these constructs. Learner goals have a significant effect only on the perceived relevance of reference frames. Knowing which factors influence students' sense-making will lead to more inclusive and flexible designs that will cater to the needs of both novice and expert learners.

Web-based simulations (WBS) are increasingly used by educators to deliver higher education curricula. Given the growing number and diversity of students undertaking study in higher education institutions worldwide, it is critical that WBS are situated within a wider social-constructivist approach that facilitates community-based learning. To this end, we argue that the community of inquiry (CoI) framework offers a suitable solution. Based on a series of interviews with university educators and emergency management practitioners this paper investigates how the CoI framework can support the effective use of WBS to deliver disaster studies curricula in the higher education context. The findings indicate that purposefully addressing cognitive, social and teaching presence within a CoI is valuable when WBS are used in higher education and emphasise a range of issues that are particular to the use of WBS and the disaster studies context.

As massive open online courses (MOOCs) shift toward professional degree and certificate programs, can they become a global on-ramp for increasing access to emerging fields for underrepresented groups? This mixed-methods study addresses this question by examining one of the first MOOC-based blended professional degree programs, which admitted students to an accelerated residential master's program on the basis of performance in MOOCs and a proctored exam. We found that male students and students with master's degrees were more likely to complete the online program and the blended program had more male students and more students with master's degrees than students in the existing residential program. Students who enrolled in the blended graduate program earned higher average grades than students in the residential program earned in their in-person courses (3.86 vs 3.75, p < .01). The findings of this study provide an example of how new online learning models can serve particular niches, but may not address broader equity challenges.

Proliferation of technology has provided additional means of out-of-class communication. This paper focuses on the relationship between technologically-mediated out-of-class communication (TMOCC) and variables crucial to successful instructional communication. A proposed model predicted perceived immediacy to mediate the relationship between immediacy behaviors (i.e., verbal and computer-mediated behaviors) and instructional outcomes (i.e., student state motivation and affective learning). While the proposed model was not supported, a model of best fit depicts perceived immediacy as a mediator for the relationship between verbal behaviors and motivation, which then impacts affective learning. The implications of these findings are discussed, as well as limitations and opportunities for future research.

Technology extends the accessibility of work integrated learning (WIL) experiences in higher education – a key strategic priority for many universities. Despite growth in the implementation of electronic WIL (eWIL) initiatives, to date no studies provide design principles to guide development of these initiatives as called for by the literature. To address this gap, this research uses a co-design approach with sixteen interviews with undergraduate and postgraduate students who had participated in eWIL. Four design principles for eWIL are proposed, including (1) authenticity, (2) integration of technology, (3) effective support processes, and (4) fostering of co-presence and relationship building. The study found student and expert academic insights from extant literature on design principles generally aligned, however, the importance of fostering co-presence and relationship building emerged from the interview data along with an expanded understanding of authenticity within the eWIL context.

This brief paper develops a series of provocations against the current forms of Learning Analytics that are beginning to be implemented in higher education contexts. The paper highlights a number of ways in which Learning Analytics can be experienced as discriminatory, oppressive and ultimately disadvantaging across whole student populations, and considers the limitations of current efforts within educational data science to increase awareness of ‘ethics’ and ‘social good’. This culminates in a stark choice: is it possible to substantially improve the field of Learning Analytics as it currently stands, or should we abandon it in favour of new forms of applying data science that are aligned with the experiences of non-conforming ‘learners’ and un-categorizable forms of ‘learning’?

Many universities use lecture capture to record live lectures and make them available online, although this practice is not without controversy. We used an online survey to investigate perceptions of lectures and their capture in staff (N = 95) and students (N = 522). We found that they valued lectures and perceived capture differently, despite similar views on the type of learning lectures best support. Students were more positive about capture, utilising the online platform effectively. Exact use differed depending on whether students were substituting or supplementing attendance. Use of lecture capture was predicted by several factors including: demand of live lectures, attendance, and performance. Student attendance ratings were predicted by the availability of online resources and difficulty in getting to lectures, whilst staff felt only availability of online resources was critical in determining student attendance. Differing views of lectures and the importance of attendance may contribute to the different overall perceptions of lecture capture in these two groups.

Developing data visualisation tools to support academics in the classroom is a challenging process due to the key requirements of usefulness and scalability, and the constraints of a university ecosystem. Here we describe the evolution of an enterprise-level, teacher-facing dashboard, designed to display data about students' enrolments and use of the Learning Management System in a meaningful way, and summarise the challenges and lessons we encountered along the way. This large university has a maturing learning analytics unit, a new, data-friendly LMS system, and data-savvy and data-hungry executive leadership. Yet the experienced pathway and evolutionary steps evidence the points that need be resolved to successfully deliver and transition to learning analytics solutions that have previously been conceptually proposed or tested at small scales in other studies. The key findings through the process highlight the level of uplift (in tech, capacity and capability) that universities need to meet contemporary demands and future possibilities.

Pre-class preparedness is critical to students' in-class learning and overall success in the flipped classroom. This study used both trace data and self-report data to identify students' pre-class learning behavior profiles and investigate the relations of the identified learning profiles with the achievement trajectory over time and students' perceived achievement goal orientations in a flipped undergraduate math class. Three distinctive types of pre-class learning profiles emerged from the study, including the lecture-focused and low time-spent profile, lecture-quiz-balanced and average time-spent profile, and quiz-focused and high time-spent profile. The results show that students' performance trajectories were significantly different among the three learning profiles. In addition, achievement goals significantly impacted the membership of the learning profiles, indicating students' perceived goal orientations shape their pre-class learning behaviors. The theoretical and instructional implications are discussed, and specific design suggestions were provided to improve students' pre-class preparedness in the flipped math classroom.

Failing to understand the perspectives of educators, and the constraints under which they work, is a hallmark of many educational technology innovations' failure to achieve usage in authentic contexts, and sustained adoption. Learning Analytics (LA) is no exception, and there are increasingly recognised policy and implementation challenges in higher education for educators to integrate LA into their teaching. This paper contributes a detailed analysis of interviews with educators who introduced an automated writing feedback tool in their classrooms (triangulated with student and tutor survey data), over the course of a three-year collaboration with researchers, spanning six semesters' teaching. It explains educators' motivations, implementation strategies, outcomes, and challenges when using LA in authentic practice. The paper foregrounds the views of educators to support cross-fertilization between LA research and practice, and discusses the importance of cultivating educators' and students' agency when introducing novel, student-facing LA tools.