Categorie archief: English Jam

Data Ecosystem Infrastructure – BSc graduate assignment

Hi Judith,

Again I have the opportunity to have some graduate students helping me with my PhD. One of them is Eddy. But he will introduce himzelf in this guestblog:

Data Ecosystem Infrastructure LA4LD

(original posted on:

Hi, my name is Eddy van den Aker and I’m currently doing my graduate internship. My project is part of Marcel’s PhD research project ( about learning analytics, learning dashboards, and learning design.


One of the problems faced by faculties, course designers, and teachers is the lack of insight into the student experience. Faculties are rated based on two factors: the time it takes for students to get their degree and the student experience. The first factor is obvious and easy to measure, but student experience is harder.

Currently the faculty of ICT within Zuyd University of Applied Science has two ways of measuring student experience. The first is the Nationale Studenten Enquête (NSE), which is a national questionnaire filled in by students from all Universities (of Applied Science). The second is a questionnaire at the end of every course, these are faculty specific.

The results of the NSE are not linked to a specific course, and the course questionnaires are done after the course has ended, so the results also come after the fact. The feedback toward the students on what is done with the results is also limited, which probably (based on anecdotal evidence) contributes to lower participation numbers. All in all, not enough data is available to improve student experience, and students are not seeing enough actionable feedback to be more engaged with the courses and the faculty.

The Project

To solve this problem Marcel has suggested creating a data ecosystem in which students, teachers and course designers participate to collect and make use off more and more useful data. Several projects have bin done and are currently going on to develop systems to collect data (for example the IoT projects Another project is looking at ways to present the data gathered in a collection of dashboards (LINK NAAR SANDERS POST).

My project fits neatly between all projects mentioned before. I will be developing an open-source infrastructure that can catch, clean, structure and store all data gathered while also delivering the underlying services needed to present the data to the users through dashboards.

Because this system sits at the core of the data ecosystem and must be able to support many different kinds of systems, both current and in the future, it is vital to make the entire infrastructure modular. During my internship, a couple of modules will be developed.

The first module will be an end-point for collecting information on student attendance. This system could be an RFID reader on which students swipe their student-card. Another module connects to the digital learning environment, in this case Moodle and collects data on how students use the provided course material. A third module imports student results from a file. And finally a last module will collect and store data from questionnaires.

As said before it has to be possible to develop more modules later down the line, adding for example environmental variables from the classroom or students study room at home. Another example would be to track the view of students in the classroom, where they are looking on the slides, what draws their attention.

Any system that collects this amount of data, especially potentially sensitive private data, has to consider the privacy of it’s participants and thus the security of the system. A way has to be sought to ensure that no one but the student themselves are able to see their own personalized data. Teachers and course designers will only see anonymised group data. The general security of the system also has to be considered.


During the development of the system I will be using a couple of different methodologies.

Design based Research Process

This project will be using the design based research methodology[1] The first three phases (problem definition & motivation, objectives of solution, and design & development) will be completed during the project, the fourth phase (demonstration) will be started.

Systematic Mapping Review

At the start of the project, a systematic mapping review[2] will be done to see in which fields data ecosystems have been suggested and maybe even deployed. It’s also interesting to know if any effect studies have been published in cases where data ecosystems have been deployed.

Scrum and GitHub

For managing the project I will be using a slightly modified version of Scrum. Slightly modified because I’m the only person in the development team. For tracking all Scrum related information I will be using the issues, pull requests, projects and wiki pages on the GitHub page for the project.

I wanted to figure out how to automate the entire Scrum workflow on GitHub. I have made some decent progress on it, good enough for this project, but I still have to move “to-do” items manually to “in progress” and after that to “in review”. If you read my post on converting exam questions to flashcard (, you know I’m lazy (in a good way, I hope) and I will be looking to automate as much as the workflow as possible, so maybe I can find a solution to these two manual actions.

Test Driven Development

For the development of the system I’ll be using Test Driven Development (TDD). The basic idea of TDD is to make testing an integral part of the development cycle. By developing automated functional and/or integration tests first, then developing smaller unit tests. at first these tests should fail (it would be weird if they didn’t). Only after having done all that, you write just enough code to get the tests to pass (or at least progress to the next step). When you have some passing tests you can refactor (improve) the code while using the previously passing tests to make sure the program does not regress. This process is often called Red, Green, Refactor.


My internship lasts half a year (20 school weeks). The first 3 weeks are spend on clearly defining the project, choosing the methodologies, and planning the phases of the project. Week 4 and 5 are used for requirements analysis and the systematic review. From week 6 until week 16 the system will be designed & developed in a couple of Scrum sprints. The last 4 weeks are used to prepare for the presentation at the end of the internship and to finish up the project in general.


The design & development phase consists of a number of sprints:

  1. Setup (software architecture & base functionality like logins, database connections, etc.) – 2 weeks
  2. Importing student results from file – 1 week
  3. Student attendance – 1 week
  4. Moodle/xAPI connection – 3 weeks
  5. MSLQ or other questionnaire connection – 1 week
  6. Admin panel – 2 weeks
  7. Wrapping up (extended testing, deployment considerations, etc.) – 2 weeks

What now?

In about 5 or 6 weeks I’ll be posting a status update on where I’m at with the project. Another 5 or 6 weeks after that I will present my results. Finally when I’m (almost) done with my internship I’ll write a post about my experiences.


The repository for this project can be found on


[1]     Peffers, K.; Tuunanen, T. (februari 2006). The Design Science Research Process. Opgeroepen van op 26 februari 2018 via:

[2]     Kitchenham, B. (2007). Guidelines for Performing Systematic Literature Reviews in Software Engineering. Opgeroepen op 14 maart 2018 via:

5 student teams working on classroom IoT

Hi Judith,

In the previous post (link: post is in Dutch) I told you that currently five teams of students are working on an IoT for learning activities proof of concept. IoT, for those who don’t know, stands for Internet of Things. With smart sensors, existing data-indicators and controllers, environments are being monitored and possibly influenced as smart as possible. In the course we are running now three different cases are presented: “Assisting elderly and their care-takers in living longer in their own home by IoT”, “Management of spaces, energy, costst of large (school)buildings”, and “LA4LD IoT”.

I am involved in all the groups but as a customer specially involved in the LA4LD IoT solution. Students should present to me a proof of concept that is applicable at Zuyd or the student’s home at the end of the course. I have five teams of students working for my assignment and I am very pleased by their enthusiasm and ideas. Students are in the proposal phase of the projects and after the holiday they have to build their proof of concept with IoT gadgets and tooling. At the HBO-ICT they don’t have to solder but can use solutions like the raspberry PI, Z-Wave or other domotica sets commercially available. They have to learn using, adapting and implementing them in the environment of the customer and then find a smart way to cope with the data or visualize the data according to the wishes of the client.

In my case they have to take into consideration that the things I want to have measured are either needed to improve the learning activities for all students or the learning process of an individual student. Some of them even embrace research and solutions of environmental control (i.e. a room with a specific kind of temperature is most suited for learning efficiency). I’d like to give you a first glimpse of the ideas of two of the five groups.

Remember I specifically asked for a proof of concept that would be implementable in one or more rooms at Zuyd University before 1-9-2018.

Table 1. Idea: IoT in higher education

In the first example a classroom setting is chosen. The actions and possibilities are described in Dutch but the idea is clear. Fun part is that they have chosen to implement a Bluetooth beacon and that I had to stop them in multiple occasions, because they were coming up with ideas to use that Beacon to improve the interactive experience in the classroom. Great examples and definitely worth further exploring, but in my case it is about getting information on the learning activities designed and the learning process at hand and trying to improve both by informing students and teachers.

Table 2. Idea: IoT in Higher Education workplace of a student

In the second example I got surprised by the students, because they took up the challenge of looking into the ‘private’ workspace of the student at home (or in a library). They came up with a desk-setting and a tooling (which name I shall not tell at this moment) that is portable and can be moved and set up anywhere.

Both groups have made a bigger presentation on what they are going to do with the data and how the data indicators relate to either learning activity design or the learning process.

The groups are half way their course and still have some time to work further on this. I already bought a Raspberry Pi, a Pi cam and some sensors (still have to be delivered) so that they actually can build a set up for me to use.

I hope that the students find a way to connect with the great research done on these topics. My colleague at the OU, Daniele di Mitri ( and former colleagues Jan Schneider en Peter van Rosmalen ( have done several experiments on sensors, multi-modality and learning. Not always to get a broader picture of the design of the learning activity (sometimes on the learning process or learning experience) but worth of reading and using. Let’s see if some of them read this blog ;).

In my LA4LD project these are the first steps in this area. As we have a lector smart devices and a lector Internet of Everything at Zuyd there are a lot more steps to take. I am looking forward to tell you about them.

With kind regards,

Marcel Schmitz

Opportunities and Challenges in Learning Analytics for Learning Design

Hi Judith,

Wouldn’t it be great to be able to give insight in how students perform and like a certain learning activity? As a teacher I often ask them how did they like several learning activities during a coffee break or one of our social activities. As an institution we ask them after an Educational period of 10 weeks with a survey. This survey (called blokenquete) has one question in it about all of the learning material in the course. Besides the extra comments students can make in general there isn’t a question on separate learning activities.

Wouldn’t it be great to be able to give teachers but also students insight in how students perform in and like the learning activities they are provided. I believe that this would help students to increase performance and results and that teachers and institutions are able to provide better fit learning activities. Now often I only use my gut feeling or the “results” of conversation with the students at the coffee machine. It would be great to have an extra instrument, which based on data and input from students generates information on a learning activity level.

In a literature review, soon to be published and presented at the EC-TEL 2017 conference, I searched peer reviewed journals for experiments with learning analytics for learning design. I have been trying to identify opportunities and challenges in this field. I found it in three opportunities, who each have their own opportunities and challenges within them.

  1. Using on demand indicators for evidence based decisions on Learning Design
  2. Intervening during the run-time of a course
  3. Increasing student learning outcome and satisfaction

In the table below I have categorized the articles I found into the three opportunities and the subopportunities and subchallenges within. I have specific tried to look for experiments and research on Learning Design, Learning Analytics, Learning Dashboards and Metacognitive Competences. This last item is interesting to me because from a Knowledge Engineering perspective the topic of “learning to learn”, which we do as we use our meta-cognitive competences is especially interesting. Taking these competences into consideration while designing a Learning Analytics for Learning Design solution seems very relevant.

After publication of the article in the Conference Proceedings I will put a link to the article here and if my presentation is ready the slides will be available here to. For now I can only share the keynote presentation of Prof. Dr. Hendrik Drachsler who is my supervisor. He talks about the place of my and my colleagues research in the world of Learning Analytics.

After this literature review on the state of the art I am going to try to design a Learning Dashboard which incorporates a Learning Analytics for Learning Design solution, which can give information during the course and which tries to make the most of the meta-cognitive competences of the students.

If I project the opportunities and challenges on a model for a solution you will get the next figure:

I will keep you posted. But feel free to ask.


Why do we want blended learning?

Hi Judith,

Thanks for your last blog about “How to support educational teams with the design of education.”   It again illustrates the difficulty of the implementation of blended learning. In the picture you use, several elements are mentioned which have influenced succesfull implementation strategies. In that graphic I miss the element of the management.

No, this is not a blog in which I want to complain about the management. I just want to try to see their point of view on this case of trying to get more blended learning. A case, sometimes struggle, sometimes a nice match, in which we have had several roles in the last few years. Their point of view is: why do we want blended learning, and do we as teachers, students and thus management want blended learning?

Quality of education is the dreamed answer, Sir Ken Robinsons’ vision of education that is not factory, which we were able to see on stage, is a wish waiting to come true. Self regulating collaborating networks of teachers and students co creating educational ecosystems is still science fiction. The managers want to dream, wish with us, they want to make science fiction into reality as well. But most of all they are stuck in that reality and sometimes we seem to forget.

The questions we have to answer aren’t how can we implement Blended Learning, as you said it yourself, that we know already. No we have to find the definite answer why do we want blended learning?

As long as we can’t translate our dreams and visions into profits, turn-over, student succes rates, student satisfaction, teacher satisfaction or regionwide knoweldge increase, management will have too much other priorities. So our real case is to illustrate the evidence there is in the context we are in so that management can dream, vision and make blended learning reality with us.

I believe that if we do, they will have a lot of fun doing it with us.

As a PhD student I will do my share, at least I will try, but I need allies. As a Zuyd community we will have to collect evidence. Not to defend our own faculty or our own model or framework which we have chosen, but to create an environment that is able to use the qualities we have to evidence based adjust our education to the demands the context or our working environments need.

Let’s go to sleep and dream on that.

Good night, Marcel Schmitz

Second week of #BlendKIT2017: Act to interact

Hi Judith,

As promised another moment to blog on the BlendKIT course activities I am doing. After reading chapter one, which I gave my comments on in the previous blog on BlendKIT2017  I also had to do some Do It Yourself assigments. I delivered a Course Blue Print and mix map for a course that I am making blended. The Blue Print gives an overview on al the course activities, course goals and course description. The discussion on learning outcomes (in Dutch) still is going, but for now I’ll manage. The Mix Map is a combination of Face 2 Face and Online elements and forces you to be aware when to choose which form.

The reading of week 2 is on blended interactions.  In this chapter a brief summary on interactions within a blended course is given. As I am trying to redesign my current course: Design Science Research, I need to keep in mind at every step how I want to interact with my students or how that I hope that the students will interact (with me/each other). Design Science Research isn’t the first topic students have in mind when they want to receiver their ICT Bachelor degree. So in the first steps of my course I need some inspiring interactions. Perhaps by experts in the field with great research examples. If the expert is an inhouse expert I can make that meeting face to face, but if it is an internationally known expert I can also consider to do a online Q&A.

Thinking about interaction all the time and designing all the parts with interaction in mind let’s us also think on which role we want to play in our course. From the literature several models are presented in which a teacher can act in such an environment: Atelier host (showing the examples of the students), network administrator (connecting people/resources), concierge (showing people where to find stuff), curational (being a knowledge keeper and collector). I believe in the participating student, who is a coach that is playing on the field. I don’t know any examples in real American sports (Baseball, American Football, Ice-Hockey, Basketball) but in soccer sometimes you see a player/coach. A trainer who is also able to play on the field himself. He takes the role of teacher/mentor on and off the pitch. In a blended course that should be the spirit, in my opinion, for a teacher to work in.

The tools that a teacher uses (not mentioned in the readings) seems to be important to. This is a rather personal question. Some like to use whatsapp or a Phone based messaging tool in a “24/7-but-only-if-I-have-the-opportunity-and-energy” agreement with the ‘class’. Others only want to communicatie through mail, fora or other communication tools delivered in a learning environment (chatbox). A teacher should be able to choose the tools in which he/she has intrinsic motivation to use. A team of teachers that is working within the blended course should be aware of each other preferences, but also be configured as a team in a way that different styles are combined. In this way more students can be reached within their own interactional comfort zone.

Interaction between students en between students and teachers delivers engagement. The readings of week 2 conclude with the question how this engagement can be measured. You can imagine Judith that seeing that question made a big smile on my face. I hope that my PhD research can help with that question. Learning Analytics, especially with regard to the learning activities can not only make the engagement, satisfaction and efficiency visible, it perhaps also can change the behavior of the student and the teacher to improve these factors.

But first things first, next step in de BlendKIT course is to work on the Course Documents of my Design Science Research course with interaction on top of my mind and I am going to make a Module Interaction Worksheet.

I will keep you posted.


Learning blended (?) about blended Learning in BlendKIT2017

Hi Judith,

First I want to introduce you to my classmates and teachers of the BlendKIT2017 Course I am participating in. We all are interested, like yourself, in Blended Learning and how to get (more) experienced in building blended course(s) material. There are several bloggers a-like who are going to share their course experiences online. I will mention them later.

Classmates, I want to welcome you to the duo-blog Judith and I share over the last couple of years. Most of it is in Dutch, because we both are IT in Education enthusiasts in the Netherlands at Zuyd University of Applied Science. But I have been blogging in English before, which you can find under the category: English Jam. Judith is the big engine in this blog, the hero that finds time in her schedule and room in her head to blog about anything she encounters at Zuyd that has to do with IT in education, innovation in education or inspiring stories in education. I, as a sidekick, am trying to keep up with her. So our course will be an opportunity to make up some ground. We write to each other in our blogposts about our experiences, so that is the form that I am going to use for our course blogs as well.

The BlendKIT2017 course is a course on Canvas. As you know I know Blackboard inside out, and I have experienced with Coursera and Edx, but I didn’t use Canvas before. So that also is a learning experience. On the first look it seems to deliver a lot of structure, but after the orientation and the first week content (being on another website) I am still have to see a lot of action to be able to make a judgement of Canvas.

The topic of week 1 is chapter 1 of the Blended Learning Toolkit. And the main discussion there is the definition of Blended Learning. As we have seen in our past projects at Zuyd that was, and still is, an issue. The most important thing is to create a common language within an institution on that topic. As we are an University of Applied Science with 10 faculties, with all of them experts and strong opinions it is important that someone makes or chooses a definition that fits all of our needs. As we are building Guidelines for our Zuyd Professional project to build blended learning courses we should reflect on how others did that. McGee and Reis have made an overview of guidelines and handbooks and have researched the elements of them ( For me the most interesting resource in the first chapter, because it illustrates the struggle in getting uniformity and gives several directions that can be taken to categorize blends or elements in a blended learning environment.

Choosing a blended learning model to build a framework upon is something that our research center Technology Enhanced Learning and our iTeam is working on. So I was glad to read that this was the road presented to us. The importance of blended learning for a university, teacher or student are different (economics and engagement from institutions, quality and engagement from students, efficiency and flexibility) but the challenge is to trigger all three with our model and framework.

For me Blended Learning is the combination of F2F and online where we choose the options based on student, teacher, institution (preferably in that order). In a dutch blogpost on designing your blend I posted a presentation on which cheat 8 illustrates a  blended strategy choosing several F2F and online items in a course. This is the way I would like to design my own blended (part of a) course. I hope I can use the next weeks of the course to work and learn on that.

Marcel Schmitz

Laatste nog te beoordelen huiswerk: Learning analytics for learning design, an opportunity for better learning.

Ha Judith,

Om je deelgenoot te maken van het laatste nog te beoordelen huiswerk van de laatste van vier online cursussen die ik nodig heb voordat ik aan mijn eindwerk mag beginnen, post ik bij deze mijn bijdrage. Het gaat over learning analytics for learning design kortom een onderwerp dat zeker past op dit blog.


Groet Marcel

Learning analytics for learning design, an opportunity for better learning.

          Despite the great success surrounding learning analytics and the increasing amount of available learning analytic tools, most educational organizations, are only aware of the potential of learning analytics regarding personalized learning and have limited experience with its application (Bichsel). All educational organizations use some form of learning design to organize their education. Analyzing the behavior and actions of students with regard to the learning design enables institutions to adapt for better learning. In order to shift the educational sector towards a more data-driven educational science, it is necessary to gain more insights in the effects of applying learning analytics in learning design.

First to illustrate, learning analytics is the field of learners data, which can be automatically harvested and analysis of these data has the potential to provide evidence-based insights into learner abilities and patterns of behavior, cognition, motivation, and emotions. The use of learning analytics to inform decision-making in education is not new, but the scope and scale of its potential has increased enormously with the rapid adoption of technology over the last few years (Siemens). At the data side, the rise of Big Data leads, in addition, to rapid development of useful techniques and tools to analyze large amounts of data. Better analysis on bigger amounts of data can be made within educational institutions by combining information across faculties. At the visualization side, better and more informative dashboards have come commercial available for institutions to use to get more insights in the actions and behaviors of students. These insights in turn can provide a crucial guidance for a more personalized curriculum design and can help teachers with the design of their education.

Secondly, illustrating Learning design as the combination of the learning activities and the support activities that are performed by different persons (students, teachers) in the context of a unit of learning e.g. a module or course. Donald et al. stated that “A learning design (product) documents and describes a learning activity in such a way that other teachers can understand it and use it in their own context. Typically a learning design includes descriptions of learning tasks, resources and supports provided by the teacher. learning design is also the process by which teachers design for learning, when they devise a plan, design or structure for a learning activity” (179). In further detail, developing a learning design a teacher or educational designer works on all phases of an instruction; starting from the definition of prior knowledge prerequisites of the target student group, design of learning objectives and outcomes, and design of the assessment to test if the outcomes have been achieved. In between are many choices for appropriate learning activities and sequences, content, teaching methods, materials and other resources that contribute to achieving the learning objectives. Efforts to incorporate personalized learning into learning designs are sought, because personalized learning is a potential approach to meeting future educational needs. Little educational concepts embed tools into their learning design to optimize personalized learning. Thus, little knowledge considering the actual use of learning analytics in educational practice and its contribution for educational theories is available (Wise). A lot of opportunities are available to improve the usage of learning design.

After illustrating learning analytics and learning design, the potential of the combination of them both, to improve education to a more personal level can be shown. The teaching activities and resources evolving from the learning design are provided increasingly over IT infrastructures and are most of the time also digitally available. This offers opportunities to use learning analytics as part of the learning environment and the learning design (Lockyer). It is of crucial importance for a learning analytics-supported learning design to consider potential learning analytics indicators already while designing the learning objectives and various activities (Lockyer). Like assessment procedures, learning analytics indicators should be considered in the very beginning of the development of the learning design. In that way, e.g. a ‘forum discussion’ is not only an effective learning activity on itself, but learning analytics can also provide an much more efficient and effective overview of e.g. student participation that could provide both student with self-monitoring information and make teachers more aware of the learning process of his students and adds possibilities for personalized feedback. However, a clear and user-friendly presentation of the learning analytics information is essential for the effect of it. learning dashboards are used to visually present learning performances. A dashboard can be defined as a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance (Few).  A learning dashboard can provide both teachers and students with insights in study progress and potential for improvement.

In order to apply learning analytics in learning design, learning designers must gain awareness and knowledge about the potentials and limitations of learning analytics. A comprehensive introduction to different domains that are affected by learning analytics was provided by Greller and Drachsler. They developed a generic design framework that can serve as a guide in developing Learning application in support of educational practice. The framework addresses six fields of attention that have to be addressed in every Learning analytics design: 1. Stakeholders, 2. Objectives, 3. Data, 4. Instruments, 5. External constraints, 6. Internal limitations (42). The stakeholders are the students, teachers, institutions, but also the service providers. The objectives of using analytics can be to reflect current behavior, but also to predict if for instance students potentially drop out. How open the data is that can be used and how the data that is used can be protected are part of the data field. The instruments to gather data, analyze it and intelligently perform computations upon are the fourth field. External constraints are privacy and ethics issues. And last field, the internal limitations consider the competences users bring to use learning analytics.

Besides technical implementation, the competences of users of learning analytics for learning design have to be considered in developing a solution. There are the two crucial aspects of ’awareness’ and ’reflection’ that need to be taken into account when dealing with learning analytics for learning design. The reflection on presented analytics results is not possible without awareness which in turn depends on some form of feedback to the user. According to Endsley being aware of one’s own situation is a three level process and a prerequisite for making decisions and effectively performing tasks: the perception of elements in the current situation is followed by the comprehension of the current situation which then leads to the projection of a future status (32). Reflection can promote insight about something that previously went unnoticed and lead to a change in learning or teaching behavior. Verbert et al. emphasize the importance of these aspects in their four-stage process model for learning analytics applications: awareness, reflection, sense making, and impact (1500). Technology, thus, is not the only aspect of implementing a learning analytics for learning design solution, the competences of the users is an equally important aspect.

In conclusion, more applications of learning analytics in learning design are an opportunity to increase learning experiences for students. This development is both an effort on implementing the currently available data analytics technology in an educational context, and an effort to invest in supporting competences of the users of learning analytics for learning design applications. Succeeded in these challenges will deliver a more personalized learning environment and thereby better learning efficiency and satisfaction for students.

Works Cited

Bichsel, J. “Analytics in Higher Education: Benefits, Barriers, Progress, and        Recommendations.” EDUCAUSE: Center for Applied Research, 2012, pp. 1–31.

Donald, C., Blake, A., Girault, I., Datt, A., & Ramsay, E. “Approaches to Learning Design:

past the head and the hands to the HEART of the matter.” Distance Education, 2009, vol. 30 no. 2, pp. 179–199.

Endsley, M.R. “Toward a Theory of Situation Awareness in Dynamic Systems.” Human

Factors, 1995, no. 37, pp. 32–64.

Few, S. “Information Dashboard Design.” The Effective Visual Communication of Data Sebastopol, 2006, no. 1, pp. 223.

Greller, W., Drachsler, H. “Translating learning into numbers: A generic Framework for

Learning Analytics.” Educational Technology & Society, 2012, vol. 3, no. 37, pp. 42–57.

Siemens, G. “Learning Analytics: The emergence of a Discipline.” American Behavioral

Scientist, 2013, vol. 10, no. 57, pp. 1380 – 1400.

Verbert, K., Duval, E., Klerkx, J., Govaerts, S., Santos, J. “Learning Analytics Dashboard

Applications.” American Behavioral Scientist, 2013, vol 10. no. 57, pp. 1500–1509.

Wise, A., Shaffer, D. “Why Theory matters more than ever in the age of Big Data.” Journal

of Learning Analytics, 2015, vol. 2, no. 2, pp. 5–13.

The basics of my PhD research

Hi Judith,

You know that I have been trying for a while to get a PhD research started. You also know that I didn’t get the funds or that my job as teacher/part of the management team had more priority. As I have written in this blog more often I tried to do my research on Gamification. Health care is a great context to use that in, but I didn’t manage to get the funds necessary. It brought me a great Healthcare and IT project where I can do some Gamification Research in, but not a PhD position.

Sometimes you have to wonder in new environments to get back to your roots. That basically is what happened in the last years. A sort of homecoming is what happened in the last months. I have a PhD research spot now at our research team Technology Enhanced Learning (Technologie-Ondersteund Leren in Dutch). In the last weeks I am finishing an internal proposal and I am ready to come out and shout aloud that I have started a research on how to use learning analytics on learning design in a run-time setting to improve student satisfaction and/or learning effectivity/efficiency.

In the next four years I am going to research an environment, say Learning Dashboard, which helps teachers and students to change or keep their behavior towards the learning design in an course. Students and teachers not only will get insight in their behavior and actions after the course but also during the run-time of the course so that we as an institution can build a more personalized learning environment for our students.

Together with the help of our Bachelor students I am going to research and develop this environment in a design science research. So the things I am going to write about are: Learning Analytics, Learning Dashboards, a little bit of Learning Design, the competences of students and teachers to be critical about the things they see in the Dashboard and the ability to interpret the information. And which techniques can we use to change the behavior of the students en teachers, so that the Learning Design is Learning Analytics driven. Or perhaps better phrased that we use our environment to enable user driven learning design. And that phrase can be in my proposal too.

So you see a work in progress but a fun one to do with all kinds of opportunities and chances to grasp. And to blog about ;). And you may reply in Dutch but I want the exercise in English.


megaNFL – The collaborative alternate reality health game of 2024

At the Games 4 Change 2014 festival, member of the board of directors, Jane McGonigal took a glimpse into the future (2024) and presented 5 nominees of the ‘Game 4 Change Of The Year Award” from 2024. Jane, known from her work at the Institute For The Future, her TED talks, her book(s) (she is gaming a new one!) and her inspiring interviews and lectures has some great potential winners for her audience.


She supports her claim for every nominee by adding up innovations or research that have recently (2014) come to the attention of the world. One of the nominees caught my attention from a games for health perspective with regard to persuading people to live healthier by using an alternate reality game: megaNFL. As I am an USA enthusiast and sports jock I could easily relate to this game which connects to American Football, but it is easily translated into other sports like soccer, (field)hockey or handball for instance.

The first exemplary innovation that is emerging now that she uses to support her claim are the rise of gadgets and wearables that track your activity (and other body related signals). Wearable tech like: Nike+ Fuelbands, Samsung watches, Moves apps on your phone, the rise of measuring humanly produced signals is upon us. One small step for technology, one giant leap for alternate reality gaming! With the data and information collected competitions and battles can be created, often against each other or against groups.


Often these competitions are based on the miles/kilometers that your run, on how often your run, or how fast you run. But there are a few examples of storytelling and creating an immersive alternate reality. On of them is the second addition Jane shows in her claim: Zombie Run . When using this app during your runs, you get special assignments to run to a special route or distance to collect ammo, medicine or weapons that can be used against Zombies that are haunting your real life environment. It also occurs that the Zombies can attack you and that you have to run from them! In this way behavioral change is motivated by alternate reality gaming.


The third addition in the claim is the popularity of fantasy sports games. Millions of people worldwide play with a fantasy NFL team, a fantasy soccer team, a fantasy formula 1 or even a fantasy field hockey team. Some of the games are connected to real world players, some aren’t, some are for money, some are just for fun. In these games you manage a virtual team and you have to manage all aspects of that team (and some even club management). Rewards can be won or bought that improve your players, team or club. It is easy to imagine a game where real world physical actions can lead to rewards in the virtual world. An example of that is the American Horsepower Challenge where children can buy clothes and upgrades for their (horse) avatar by doing physical exercise.

A great innovation according to me and we don’t have enough of this types of games for every age group, but we are watching the award show of 2024 and Jane wouldn’t be Jane if she goes onto the next level of immersion. megaNFL let’s you collect ‘resources’ and ‘rewards’ by doing something good for the human body (as does Zombie Run or the American Horsepower Challenge), but the rewards aren’t used in a virtual world, but in the real world. In megaNFL you can ‘win’ an extra down for your team when you (and your group) reaches the goal or beats the contester (or group) of the other team. Translated to soccer that would be that the fans of Manchester United are doing a ‘who runs the most’ competition against the fans of Bayern Munich. The winner of that contest wins a corner kick for their team, or a real 12th player for the last 5 minutes of the game. Jane uses a fourth addition in her claim to support why the board members of the NFL, FIFA or field hockey federation would change their rules by 2024 to let the supports have such an impact on the games. In this addition she mentions the law suits on brain damage that were a big topic in the last NFL season (brain damage also is a problem in soccer and field hockey). As someone who has got “SuperBetter” from a brain injury she hopes that the NFL will feel the moral obligation to participate in such a step. Let’s hope they will. I sure would to like to see (a kind of) megaNFL.

What about you?


Sometimes a little tweet from someone else is enough…

Hi Judith,

Today no long stories from me. 😉 Aaah! I have read your paper but will only react on this blog when you have published it online. I have some discussion points as you know, but will discuss them when you kick the ball to me 🙂

A short story from a old student of mine. Stefan Dalemans has, as an employee of Mediaan, tweeted about an article that mentiones 5 ways to build company culture with a virtual team. Great tips which are defenitly valuable for our MOOC project. So emjoy (and kudos to Stefan)

To get you excited, these are the 5 ways, explanation in the link in the tweet.

1. Build or but the right tools and enforce them

2. Make them WANT to engage

3. Bring the mountain to the home office

4. Make them interact in their community (and benefit from their distance)

5. Make the base employees want to work with them (and distract them)

Good night!


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