Thinking about course design

I have been thinking about designing University courses in an age of open educational resources.

My particular interest at the moment is the combination of data science and sport analytics.

I keep returning to the idea of a ‘pedagogical technologist‘ able to offer ‘structured exposure’ to learners who might not otherwise choose to attend university. I see structured exposure as the key here if we are to offer a service to students in an institutional setting.

My inspiration is Alan Levine.

In 2014, Howard Rheingold described Alan as a pedagogical technologist “an architect of open, connected learning systems that enable students to take power over and responsibility for (and joy in!) their own learning”.

Howard added “Many people have something to say about what to do with the educational opportunities afforded by digital media. Fewer can persuasively articulate a case for specific pedagogies that digital media enable”.

I think Alan does this profoundly well.

Howard observed “while schools no longer have a monopoly on learning because free digital media can be used to learn anything, knowing what to learn, how to learn, what questions to ask, isn’t a given, even with the savvy online self-learner. The role of the instructor has not gone away, but it has shifted …”

This shift came to mind this morning when I read Bharath Raj’s How to play Quidditch using the TensorFlow Object Detection API.

I wondered how I might engage students like Bharath should he want to extend his domain knowledge to sports other than Quidditch as he guided his readers “through creating your own custom object detection program, using a fun example of Quidditch from the Harry Potter universe! (For all you Star Wars fans, here’s a similar blog post that you might like)”.

In his post he noted:

My motive was pretty straightforward. I wanted to build a Quidditch Seeker using TensorFlow. Specifically, I wanted to write a program to locate the snitch at every frame.

But then, I decided to up the stakes. How about trying to identify all the moving pieces of equipment used in Quidditch?

I though any design for learning I might propose would need to be profoundly personal. In this case, I wondered how prospective students might be introduced to object detection in sport using Bharat’s blog post as a problem finding start to a learning journey that encompassed first principles and granular detail.

I thought I might extract some provocations from the post and suggest students go back to some early work by Janez Pers and his colleagues (2002) and on to some of the more recent ‘ghosting’ studies of basketball and football.

This could become a spontaneous hackathon. At the University of Canberra, for example, I imagine this being facilitated by Roland Goecke in ways that underscored the power of structured exposure.

I hope students and teachers would have personal and shared learning journals that make transparent the emerging understanding about big things and small things. In doing so, we would all be moving toward a world that will be rather than a world that was.

I sense that pedagogical technologists are at home in this world of emerging performances of understanding. It is a fallible environment that demands institutions themselves become much more agile and much more imaginative in ways that courses are designed and assessed.

Photo Credits

Music abducted me (Carlos Romo, CC BY-NC-ND 2.0)

Alan Levine on/of the web (Kristina Hoeppner, CC BY-SA 2.0)

A model Fenway Day (Brian Talbot, CC BY-NC 2.0)

Graduate Certificate in Sport Analytics at the University of Canberra

3b4d8237f7217c1737fa633774867e8cJocelyn Mara has created a Graduate Certificate in Sports Analytics at the University of Canberra.

The University website has this link to the course.

I am excited by this development. Jocelyn will add a distinctive voice and approach to the sharing of insights into the analysis of performance.

I was fortunate to meet her during her undergraduate study at the University and then watched with admiration as she completed an Honours’ project in performance analysis, became a performance analysis scholar at the Australian Institute of Sport and received her PhD.

In addition to her research interests, Jocelyn has also explored the possibilities of creating open educational resources.

With her permission I would like to share some news of the graduate certificate.

Jocelyn writes:

I will be encouraging a Bring Your Own Software approach to the course, as I will be using Open Source software such as RStudio and LongoMatch. Students will have access to Tableau. I will also be using Excel quite a lot throughout the course.

I preparing a MOOC to run on the Canvas Network which will be a 4-week taster of the entire Graduate Certificate (one week for each unit). This will commence in January 2017.

I am delighted with the open aspects of the course. Jocelyn is discussing how her approach might fit in with Roland Goecke‘s work at the University of Canberra to offer a Masters in Data Science with a Sport Analytics strand.

This is the content of the Graduate Certificate course in Sports Analytics:

Unit 1: Performance Analysis in Sport

1.1 Identifying Performance Indicators

1.2 Designing Observational Systems and Collecting Data

1.3 Data Analysis and Interpretation

1.4 Feedback and Communication

Activities

  • Collecting sports data
  • Analysing data
  • Visualising data
  • Online quiz
  • Match Analysis assessment

Unit 2: Athlete Monitoring

2.1 Player tracking

2.2 Monitoring athletes with self-report systems

2.3 Training load and injury

2.4 Performance testing

Activities

  • Analysing player tracking data
  • Analysing RPE and well-being data
  • Monitoring training load
  • Analysing performance testing data
  • Online quiz
  • Athlete monitoring assignment

Unit 3: Applied Data Analysis in Sport

3.1 Data management and transformation

3.2 Determining associations

3.3 Predicting outcomes

3.4 Determining differences

3.5 Data visualisation

Unit 4: Sport Informatics and Analytics

4.1 Introductions

4.2 Pattern recognition

4.3 Performance monitoring

4.4 Audiences and messages

Activities

Formative ePortfolio to document engagement with unit 4.

I am hopeful that many of the resources I have been aggregating and curating will be supportive of Jocelyn’s work, particularly with unit 4 and this WikiEducator resource.

I hope this course is of interest to the sport industry. One of my ideas is that we support people who are in sport by offering flexible and open learning opportunities. I acknowledge too that some people might like a fee-for service structured attention opportunity that aligns them closely with a university and provides blended learning experiences.

I think that Jocelyn’s work can articulate with other institutions and communities of practice as each of decides how we continue to learn.