Learner Support Patterns and Strategies: Presentation

I presented at the International Conference on e-Learning (ICEL) this morning. The conference was hosted by the Cape Peninsula University of Technology (CPUT) in Cape Town, South Africa. The presentation looked at research done at the Open University of Catalonia and the University of South Africa around students’ use of different devices and personal technologies and what support they need.

 

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SCOPUS eLearning and ODL Journal Rankings

The SCImago (by SCOPUS) journal rankings for 2017 have recently been released. I have gone through the Education category and listed the journals that are relevant for research in e-learning and open and distance learning. The list is organised by quartile and each journal shows the impact factor or journal ranking and whether it is an open access journal. The SJR ranks journals by number of citations and their average prestige per article.

2017 SCImago Journal Rank by Cite Score (Category: Education)

Quartile 1

  • Internet and Higher Education – 3.35
  • Computers and Education – 2.63
  • Learning, Media and Technology – 2.30
  • International Journal of Computer-Supported Collaborative Learning – 1.59
  • Journal of Computer Assisted Learning (JCAL) – 1.40
  • British Journal of Educational Technology (BJET) – 1.34
  • Journal of Research on Technology in Education – 1.31
  • International Review of Research in Open and Distance Learning (IRRODL) – 1.26 (Open Access)
  • Educational Technology Research and Development (ETRD) – 1.22
  • Educational Technology and Society (ETS) – 1.09 (Open Access)
  • Technology, Pedagogy and Information – 0.89
  • International Journal of Mobile Learning and Organisation – 0.85
  • Research in Learning Technology – 0.78 (Open Access)
  • IEEE Transactions on Learning Technologies – 0.78
  • Australasian Journal of Educational Technology (AJET) – 0.72 (Open Access)
  • American Journal of Distance Education – 0.71
  • Distance Education – 0.70
  • Interactive Learning Environments – 0.66

Quartile 2

  • Journal of Educational Computing Research – 0.65
  • Technology, Knowledge and Learning – 0.61
  • Online Learning – 0.58
  • Open Learning – 0.58
  • Journal of Interactive Online Learning – 0.50 (Open Access)
  • Knowledge Management and E-Learning – 0.49 (Open Access)
  • International Journal of Lifelong Education – 0.49
  • Electronic Journal of e-Learning – 0.44 (Open Access)
  • Education and Information Technologies – 0.40
  • International Journal of Educational Technology in Higher Education – 0.39 (Open Access)

Quartile 3

  • International Journal of Mobile and Blended Learning – 0.33
  • Journal of Information Technology Education:Research – 0.32 (Open Access)
  • e-Learning – 0.31
  • International Journal of Distance Education Technologies – 0.28
  • Journal of Educators Online – 0.28 (Open Access)
  • International Journal of Web-Based Learning and Teaching Technologies – 0.25
  • International Journal of Technological Learning, Innovation and Development – 0.23
  • International Journal of Technology Enhanced Learning – 0.23
  • International Journal of Information and Learning Technology – 0.23
  • Digital Education Review – 0.22 (Open Access)
  • International Journal of Emerging Technologies in Learning – 0.22 (Open Access)
  • International Journal of Interactive Mobile Technologies – 0.21
  • Journal of E-Learning and Knowledge Society (JeLKS) – 0.20
  • International Journal of Information and Communication Technology Education –  0.20
  • Interactive Technology and Smart Education – 0.19

Quartile 4

  • International Journal of Learning Technology – 0.18
  • Turkish Online Journal of Distance Education – 0.18 (Open Access)
  • Turkish Online Journal of Educational Technology – 0.16 (Open Access)
  • International Journal of Virtual and Personal Learning Environments – 0.15
  • Ubiquitous Learning – 0.14
  • International Journal of Technologies in Learning – 0.11

Innovative Pedagogy 2017

The Innovative Pedagogy 2017 report explores new forms of teaching and learning in a digital world, and looks at 10 innovations that have not yet influenced post-school education. This is the sixth annual report produced by the Open University in the UK. This year the report was produced in collaboration with the Learning In a NetworKed Society (LINKS) Israeli Center of Research Excellence (I-CORE). The 10 innovations are listed in the order of possible widespread adoption.

  1. Spaced learning: It is known that we learn facts better in a series of short chunks with gaps between them, rather than in a long teaching session such as a lecture.  Recent research in neuroscience has uncovered the detail of how we produce long-term memories. This has led to a teaching method of spaced repetition that occurs in the following order: (1) a teacher gives information for 20 minutes; (2) students take a break of 10 minutes to participate in an unconnected practical activity such as aerobics or modelling; (3) students are asked to recall key information for 20 minutes, followed by a 10-minute break; and (4) students apply their new knowledge for a final 20 minutes. A study of spaced learning shows a significant increase in learning compared to a typical lesson.
  2. Learners making science: Citizens need the skills and knowledge to solve problems, evaluate evidence, and make sense of complex information from
    various sources. A strong understanding of Science, Technology, Engineering,
    and Maths (STEM) topics can develop these skills. Enabling learners to experience how Science is made can enhance their content knowledge. It can also develop scientific skills, contribute to their personal growth, and result in identity change and an increased understanding of what it means to be a scientist. These changes can be achieved through participation and contribution to citizen science activities that are personally relevant, promote engagement with both social and natural sciences and scaffold understanding of the scientific method, critical thinking, and reflection.
  3. Open textbooks: Open textbooks are freely shareable and editable resources
    designed to operate in place of a specified textbook. As one approach to open educational resources (OER), they are not locked down by copyright restrictions but have an open licence that enables everyone to reuse, remix, revise, redistribute and retain them. These books are adaptable – not fixed and static resources but  dynamic ones. Students can edit and amend an open textbook as part of their study. This helps them to understand knowledge as an ongoing process in which they play an active role. These textbooks can be seen as part of a broader move towards ‘open pedagogy’, which emphasises open content and open practices.
  4. Navigating post-truth societies: Fake news and information bubbles are not
    new but awareness of their impact on public opinion has increased. People
    need to be able to evaluate and share information responsibly. One response
    is to integrate these skills within the curriculum. However, how can we know which sources to trust? The ways in which people think about such questions are called ‘epistemic cognition’. Researchers have developed ways of promoting learners’ epistemic cognition. These include promoting understanding of the nature of knowledge and justification as well as fostering abilities to assess the validity of claims and form sound arguments.
  5. Intergroup empathy: Online environments, such as social media, form global virtual spaces. In these, people from different backgrounds interact with each other, even if they come from countries or cultures that are engaged in conflict. This means that skills such as communication, teamwork, and empathy are important. An ‘us’ versus ‘them’ perspective makes it difficult to empathise – to understand and share the feelings of members of the other group. The effects of intergroup conflicts can spill over into online communities, provoking strong negative emotions and the use of stereotypes. In such cases, activities designed to promote intergroup empathy can provide effective responses and help to reduce tensions.
  6. Immersive learning: Learning based on experience and exploration can be
    intensified through immersion. It can enable people to experience a situation
    as if they were there, deploying their knowledge and resources to solve a
    problem or practise a skill. The learning comes from integrating vision, sound,
    movement, spatial awareness, and even touch. By using technologies such as virtual reality, 3D screens or handheld devices, learners can experience immersive learning in a classroom, at home, or outdoors. This enables them to explore possibilities that would be difficult, dangerous, or impossible in everyday life.
  7. Student-led analytics:  Learning analytics make use of the data generated during study activity in order to enhance learning and teaching. They often focus on how teachers and institutions can help learners to pass a test, a module, or a degree. Student-led analytics, on the other hand, not only invite students to reflect on the feedback they receive but also start them on the path of setting their own learning goals. These analytics put learners in the driving seat. Learners can decide which goals and ambitions they want to achieve, and which types and forms of learning analytic they want to use to achieve those targets. The analytics then support learners to reach their goals.
  8. Big-data inquiry: thinking with data: New forms of data, data visualisation and human interaction with data are changing radically and rapidly. As a result, what it means to be ‘data literate’ is also changing. In the big data era, people should no longer be passive recipients of data-based reports. They need to become active data explorers who can plan for, acquire, manage, analyse, and infer from data. The goal is to use data to describe the world and answer puzzling questions with the help of data analysis tools and visualisations. Understanding big data and its powers and limitations is important to active citizenship and to the prosperity of democratic societies. Today’s students therefore need to learn to work and think with data from an early age, so they are prepared for the data driven society in which they live.
  9. Learning with internal values: Throughout life, significant learning is triggered, monitored, and owned by us as individuals. This learning is rooted in our own needs and interests and shaped by our internal values. However, schools and a national curriculum need to conform to a set of external values. These are unlikely to align exactly with the learning that is based on individual students’ internal values. Efforts have been made to design and develop programmes that can meet this challenge. The main approach offers students choice about what and how they learn. At the same time, it equips them with means to develop appropriate  knowledge, skills and ways of thinking in order to support their learning. This approach balances the learning based on students’ internal values with the learning that is required by the normative values of educational systems.
  10. Humanistic knowledge-building communities: The goal of humanistic education is to help people become open to experience, highly creative, and self-directed (person-centred). Knowledge-building communities aim to advance the collective knowledge of a community (idea-centred). When the two approaches are combined, they create a new one: humanistic knowledge-building communities. Students can develop their knowledge and selves in integrated and transformative ways.

 

Reference:
Ferguson, R., Barzilai, S., Ben-Zvi, D., Chinn, C.A., Herodotou, C., Hod, Y., Kali, Y., Kukulska-Hulme, A., Kupermintz, H., McAndrew, P., Rienties, B., Sagy, O., Scanlon, E., Sharples, M., Weller, M., & Whitelock, D. (2017). Innovating Pedagogy 2017: Open University Innovation Report 6. Milton Keynes: The Open University, UK.

Learning Analytics and Evidence in Higher Education

The Department of Education at UOC recently organised a seminar on the role of evidence-based research in higher education on 22 November 2017. Prof Paul Prinsloo, UNISA, South Africa, provided the keynote address at this seminar. These are my notes from his address:

Learning analytics in a time of an insatiable thirst for data and evidence: A provocation

  • Rather than focusing on whether the future of higher education will be evidence-based, it may be more important to consider: why is there a need for evidence? Who defines what counts as evidence and what does not count as evidence? Who verifies the evidence as valid and appropriate for the associated purposes and contexts? Who will use the evidence and how? And how does evidence impact the collection, analysis and use of student data?
  • Data is collected, analysed and used to inform or support pedagogy and learning. This data is collected throughout a student’s learning journey and ultimately tracks if students succeed or fail:
    • Descriptive: what happened/is happening
    • Diagnostic: why did it happen
    • Predictive: what will happen
    • Prescriptive: how can we make it happen
  • Questions are needed as to what data is needed to describe, understand, predict and prescribe the learning journey. Some data we have already, some data we need obtain still. But ultimately we should be asking what data do students themselves need to make better informed choices and take ownership of their learning journey.
  • The understanding of learning analytics as a process of collecting evidence and measuring success or efficiency is shaped by our understanding and descriptions of students and learning. For example, are students sick/broken and need to be healed? (no!).
  • What is the impact of learning analytics? More successful/satisfied students, more effective teaching or better utilisation of resources. For learning analytics to succeed, evidence is needed, but is this evidence there?
  • Evidence is: Contested (evidence may not align with values or beliefs), Political (evidence may exist, but the political will to take action may not), Incomplete and Fragile.
  • For several years, learning analytics has been touted as bringing about a revolution in education. Yet the “revolution” has not occurred.

Provocations for thinking about evidence

  • How do we think about evidence in a world saturated with information? (what to ignore vs what is worth knowing)
  • How do we think about evidence in a world of fake news and alternative facts?
  • How do we think about evidence in a world where “knowing” is distorted and manipulated to create biased and distorted findings?
  • How do we think about evidence in a world where “what we know” is increasingly determined by algorithms and automated agents (Facebook, Google, Amazon)?
  • How do we think about evidence in a world where “knowing” does not imply action?
  • How do we think about evidence in a world where “knowing” does not mean we have the capability or resources to respond?
  • How do we collect evidence in a world where effectiveness/efficiency does not mean an intervention was appropriate, moral or ethical?
  • How do we present evidence in a world where it will only be considered if it is practical and feasible?

Pointers

  • Learning analytics as moral practice: Just because you can collect their data, does not mean that you have to.
  • Change the narrative: whose story is it anyway? Analytics could become our voiceover of the student experience… instead of listening to students.
  • It is also our story and we need to respond… the obligation to act.
  • Recognise the political nature of data and evidence.
  • Consider the differences between correlation and causation in complex and dynamic systems.
  • Oversight and accountability.
  • Yet we cannot NOT afford to collect, analyse and use student data.

 

There was lots to think about from this presentation, but I think a key take away for me was to (re)consider and be reminded that as educators, we need to focus on: what data do students themselves need to make better informed choices and take ownership of their learning journey?

 

ECAR 2017 Student and Faculty Technology Research Studies

The EDUCASE Center for Analysis and Research (ECAR) recently released their annual studies of students and faculty use of technologies in higher education. The following sections highlight the key findings from each report:

2017 Study of Undergraduate Students and Information Technology

  • Students rate their overall campus technology experiences favorably, such as wireless network performance.
  • When it comes to meeting technological support needs, students’ default is DIY. Students are more than twice as likely to figure out solutions to technology problems on their own, to search online sources, or to ask a friend than they are to use their campus help desk.
  • Laptops are king, smartphones are queen, and tablets are on the way out. Almost all students own a laptop or a smartphone, and 3 in 10 students own a laptop, a smartphone, and a tablet. Students view their laptop as critical to their academic success, and three-quarters of students said their smartphone is at least moderately important. Tablets appear to be in decline in terms of ownership, utility, and importance, in part because their functionality is duplicated by a combination of laptops and smartphones.
  • Students’ experiences with their instructors’ use of and approach to technology in the classroom are mixed.
  • Students are pleased with the student success tools available to them. At least 80% of students think that every student success technology asked about—from degree audit, planning, and mapping tools to early-alert systems, self-service tools, recommendations for courses, and suggestions about academic resources—is at least moderately useful.
  • The number of students preferring a blended learning environment that includes some to mostly online components has increased. The number of students preferring completely face-to-face or completely online courses continues to dwindle.
  • Students are satisfied with features of their LMS… except when they aren’t. Students have favorable opinions about the basic features and functionalities of their LMS. But, the more sophisticated the task and the more engagement required of students, the less happy they tend to be. This may be a function of the tools, the instructors who use them, or both.
  • Students would like their instructors to use more technology in their classes. Technologies that provide students with something (e.g., lecture capture, early-alert systems, LMS, search tools) are more desired than those that require students to give something (e.g., social media, use of their own devices, in-class polling tools).
  • Students reported that faculty are banning or discouraging the use of laptops, tablets, and (especially) smartphones more oſten than in previous years.

2017 Study of Faculty and Information Technology

  • Faculty are quite happy with the technology and support provided by their institution.
  • Technology training offered to faculty is an opportunity to “train the trainers.” When seeking technology support, faculty prioritize information sources that they perceive as signifying expertise.
  • Faculty are critical to raising awareness among students about technology training available. Such technology training is critical for student success.
  • Faculty have confidence in their institution’s ability to safeguard their data and that of their students. The institution’s actions to safeguard this data, however, are largely invisible to faculty.
  • Many faculty buy their own personal computing devices. Most institutions provide faculty with a laptop or a desktop, yet many faculty additionally buy themselves a personal laptop, and nearly all faculty own a personal smartphone.
  • Despite the increasingly widespread use of student success management
    systems in higher education, many faculty do not use them. This, despite
    these systems’ potential to inform faculty members’ teaching and advising.
  • The LMS that is implemented at an institution has little impact on faculty members’ use of it or their satisfaction with that use. Faculty use their institution’s LMS at high rates but mostly only for operational, course management functions like circulating information such as the syllabus, handouts, and assignments.
  • Faculty predominantly teach courses with no or only some online components, and this is how faculty members prefer to teach courses. Yet most faculty believe that they could be more effective instructors if they were better skilled at integrating various technologies into their courses. Media-production software and open educational resources (OER) top this list.
  • The greater a faculty member’s skill in classroom management, the more likely the faculty member is to encourage or require students to use devices in the classroom. A large percentage of faculty either discourage or outright ban computing devices of all types from their classroom.

Research Trends in Mobile Learning in Higher Education: A Systematic Review of Articles

This post provides a matrix of 233 mobile learning articles (Article Matrix of Mobile Learning Studies spreadsheet) published in peer reviewed journals between 2011 and 2015. It provides supplementary information for an article published in IRRODL:

Krull, G., & Duart, J. (2017). Research Trends in Mobile Learning in Higher Education: A Systematic Review of Articles (2011 – 2015). The International Review Of Research In Open And Distributed Learning, 18(7). doi:http://dx.doi.org/10.19173/irrodl.v18i7.2893