Hans Poldoja: Doctoral Dissertation


Hans Poldoja of Aalto University has successfully defended his Doctoral Dissertation entitled: “The Structure and Components for the Open Education Ecosystem: Constructive Design Research of Online Learning Tools”. I was happy to see that it was supervised by Teemu Leinonen whom I met at Eden last June. Congrats!

Poldoja examines: “five design projects of online services & learning tools in regard to four perspectives: Technology-Enhanced Learning (TEL), Open Education (OE), Digital Ecosystem (DE) and Design Research (DR)”.

TEL: 1990’s, digital tech in learning, complex, interdisciplinary field (social sciences, technology, design), sub-areas include computer-supported collaborative learning, improving practices of formal education, informal learning, interoperability of tech learning services, personalization of learning etc.

OE: making educational assets visible and accessible and harnessing the collective wisdom of a community of practice and reflection (Iiyoshi & Kumar: 2008), with a licensing model that grants users with more permissions or an open environment or process, learners as active creators. (progressive inquiry pedagogical model)

DE: Web 2.0, web and mobile apps, preferred set of tools for each user, communication between users, “distributed, adaptive open, social-technical systems, with properties of self organization, scalability and sustainability, inspired by natural ecosystems”. “Briscoe and De Wilde: 2009)

DR: as in planning and giving form to new products, challenges are addressed through practice.

Poldoja focuses his research on the design of online learning tools and their mandatory incompleteness; OL tools, he says, are designed to be open and flexible for users to freely combine, however, under uncertain requirements.

His design case studies include:

  • PILOT: multimedia learning resource template, open educational resources, European school education
  • LeMill: web community for authoring and sharing of open educational
    resources, open educational resources, European school education
  • EduFeedr: coordination tool for blog-based online courses, open online courses, higher education & teacher training Estonia
  • LeContract: learning contract planning tool, open online courses, higher education & teacher training Estonia
  • DigiMina: self- and peer-assessment tool, assessment of educational technology competencies for Estonian teachers

Looking forward to reading it all. I’ll be back for more.

Heuristics & Cognitive Biases


Heuristic (adj): searching to discover

Heuristics: thinking relying on the use of intuition, human feel, experience, rules of thumb, examples by analogy for judgemnet and decision making in real life conditions, without normative analysis based on mathematical representation. (Tversky and Kahneman 1982; Schon 1983)

Heuristics are used to reach quick, reasonably effective, and creative solutions, but they may also lead to errors and fail because of cognitive biases (e.g. Tversky and Kahneman 1982a; Baron 1994; Evans 1995; Osherson 1995), which are unwarranted confidence in believing the likelihood of an outcome.

Frequent Biases or illusions of Validity:

  • Representativeness: rely on similarity
  • Availability: based on the ease of recall and imaginability, top down bias where the way information is stored in memory has misleading effect on the way we access it.
  • Anchoring and Adjustment: dependence on adjustment from an initial value
  • Insensitivity to predictability

Debiasing Strategies:

  • making the task easier
  • teach probability estimation skills
  • consider alternatives
  • decrease reliance on memory
  • warning of the possible biases at work
  • the rebuttal or disqualification  mecchanism, thinking about exception


References & Image

Bay, Joo-Hwa, 2001, ‘Cognitive Biases on Design: The case of tropical architecture’, PhD Dissertation, Technische Universiteit Delft