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Month: July 2020

H817 – 20b – Block 4 – Week 23 Activity 14 – Network Diagrams – PART 1

H817 – 20b – Block 4 – Week 23 Activity 14 – Network Diagrams – PART 1

Read this short paper that provides an introduction to social network visualisations and to the SNAPP tool: Bakharia et al. (2009), Social networks adapting pedagogical practice: SNAPP. In your learning journal, or blog, make a note of the things that can be revealed by a network diagram of students’ discussions. The authors identify six – you may be able to think of more. Use these as headings and, under each one, note how this information could be used to support…

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H817 – 20b – Block 4 Activity 13 – Social Analytics

H817 – 20b – Block 4 Activity 13 – Social Analytics

* Prepare slides for a ten-minute presentation that can be used to explain to staff what social learning analytics are, why they are becoming more important and the benefits they may offer. Use suitable software, such as PowerPoint, Keynote, Prezi or something else you know well. [ngg_images source=”galleries” container_ids=”2″ display_type=”photocrati-nextgen_basic_thumbnails” override_thumbnail_settings=”1″ thumbnail_width=”120″ thumbnail_height=”80″ thumbnail_crop=”1″ images_per_page=”0″ number_of_columns=”4″ ajax_pagination=”0″ show_all_in_lightbox=”0″ use_imagebrowser_effect=”0″ show_slideshow_link=”1″ slideshow_link_text=”[Show slideshow]” order_by=”sortorder” order_direction=”ASC” returns=”included” maximum_entity_count=”500″]My target audience for this presentation would be lecturing and professional development staff in my…

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H817 – 20b – Week 22 – Activity 12 – Checkpoint and Process Analytics

H817 – 20b – Week 22 – Activity 12 – Checkpoint and Process Analytics

Look through the learning outcomes and learning activities in the block, noting where/why checkpoint analytics might be used and where/why process analytics might be used. You will be writing from an informed perspective, with an eye to what you would have found useful as a learner. In looking back at Block 2 I realise that the entire course is designed in a social constructivist way. The ‘average’ activity in this block involves reading the resources provided then taking part in…

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H817 – 20b – Week 22 – Activity 11 – LA and LD

H817 – 20b – Week 22 – Activity 11 – LA and LD

Make notes in your learning journal or blog about these types of analytic and when they can be applied. Consider whether these classifications are more useful than the ones you have considered at other points this week. Checkpoint After studying Lockyer et al. (2013) I found that checkpoint analytics indicate that a student has met some prerequisite such as downloading a resource or viewing a Moodle book. This relates to the resources in learning design. Checkpoint analytics can be used…

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H817 – 20b – Week 22 – Activity 10 – Library

H817 – 20b – Week 22 – Activity 10 – Library

Make a list of the types of data collected in university libraries. These range from swipe card data about student visitors to usage figures for specific websites. As outlined in Library Impact Data Project (LIDP) (2012a) Demographics of students (mature/non-mature students) Gender of users Ethnicity Country of Domicile As outlined in LIDP (2012b) Subject studied by user (Science, Health, Arts) Number of visits Number of PDF Downloads Hours logged in to eResources As listed in LIDP (2012c) Overnight usage Number…

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H817-20b – Week 22 – Activity 9

H817-20b – Week 22 – Activity 9

In this activity we are studying the paper by Dyckhoff et al. (2013) “The authors include tables that focus on why learning analytics are used. Reflect on the questions asked by teachers (Table 1) and the goals of learning analytics (Table 4). Note in your learning journal or blog which of these questions can be considered: a.data driven b.pedagogy driven.” (A) Qualitative evaluation How do students like/rate/value specific learning offerings? (DATA DRIVEN – IF survey data is gathered) How difficult/easy…

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H817-20b – Week 22 – Activity 8

H817-20b – Week 22 – Activity 8

To recap, my definition of Learning analytics is “The timeous capture and analysis of institutional data sets, to inform immediate and long term decision making.” Having reviewed the Ferguson et al. (2019) paper, I have identified the following innovations which I believe could be supported by learning analytics. I do believe my original definition is still valid in the context of the following examples. Innovation 1 – Action Learning Action Learning could perhaps be supported by analytics. This learning technique…

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H817-20b – Block 4 – Week 22 – Activity 7

H817-20b – Block 4 – Week 22 – Activity 7

“Decide which groups of people could benefit from some of the different types of data reported by Google Analytics, and make a note in the appropriate column(s). Write a reflective piece in your learning journal or blog about how these data could be used to generate learning analytics, together with any problems that might be associated with their use in education. Make reference to any occasions on which you have been presented with or had access to any of these…

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H817-20b – Block 4 – Activity 6

H817-20b – Block 4 – Activity 6

“For each person, make a note of areas of the websites listed below that you would recommend to them, and any resources or events that would help their understanding.“ I would first of all direct all of the staff outlined to the excellent online seminar I attended in April 2020 hosted by Poquet et al. (2020). This seminar provides some useful background information on analytics in social networks, VLEs and relates these areas to learning design. It is also mentioned…

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H817-20b – Block 4 – Week 21 – Activity 5

H817-20b – Block 4 – Week 21 – Activity 5

Make a list in your learning journal or blog of the main points you would share with someone in your context, or in a context that you know well, who had asked for a brief introduction to learning analytics. Further to studying the paper by Ferguson (2020) I would initially share the basic definition of Educational Data Mining (EDM). This would involve a brief explanation of the use of data sets too large to be handled manually. I would introduce…

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