24 September 2009


Constructivistic learning claims that "all learning involves the interpretation of phenomena, situations, and events, including classroom instruction, through the perspective of the learner's existing knowledge" (Smith et al, 1993). As such, with the prior knowledge students bring into the classroom, learning involves confrontation and replacement of misconceptions that students have. (Otherwise, there is no need for them for any formal training.) But how do students recognize these misconceptions, and how can they correct these misconceptions given that misconceptions are hard to change? Traditional strategies include lectures, assignments, exams, etc. Well constructed clicker questions can be particularly effective in exposing misconceptions. We can also learn a lot from video games. Good video games (Gee, 2005) can expose players' misconceptions of the game by slowly guiding the players to gain proficiency in the game play, whether it may be motor skills required to use the controls, or mental skills to solve the problems, or awareness of hidden story lines, etc. Rewards have been used effectively to grab the player's attention. How we can turn our classroom experience into a well constructed video game remains a mystery and challenge for all instructors!

According to Smith, diSessa and Roschelle, instruction is supposed to replace misconceptions by confronting the students with their misconceptions. Instead of replacement, perhaps learners are integrating what they know and trying to resolve the conflicts they encounter when new information is presented. There may be knowledge replacement but I suspect it is more integration or resolution of these conflicts, than replacement that is going on.

McCartney et al's paper shows some of the misconceptions on how CS students determine algorithm efficiency. Given two algorithms, the students were asked which one is more efficient to solve a certain problem. The goal is to see whether they consider how the algorithms behave in the worst case - which most experts would do. Although the majority of the students pick the right algorithm, some focus on one part of an algorithm to determine the "worst" case, while others focus on another part of the same algorithm. One of the misconceptions then is that students do not really know what the worst case was. They also do not seem to think tracing through an algorithm on concrete data is important in the analysis.

What are other CS misconceptions? Computer will do what I mean. Command line is not as powerful / efficient as graphic interface. The scenes in a computer game are stored in the program rather than dynamically generated. Playing with / debugging / changing code in the process of writing a program are not expert behaviors. Doing rough work is not cool when solving problems. Web design is programming. Spreadsheet is a database. Design is useless. Testing is not valuable. Any others, there must be a whole lot more ...


Smith, J., diSessa, A., Roschelle, J., (1993), Misconceptions Reconceived: A Constructivist Analysis of Knowledge in Transition, retrieved on September 24, 2009 from http://ctl.sri.com/publications/downloads/MisconceptionsReconceived.pdf.

McCartney et al., (2009), "Commonsense computing (episode 5): Algorithm Efficiency and Balloon Testing", retrieved on September 24, 2009 from http://portal.acm.org/citation.cfm?id=1584322.1584330.

Gee, J. (2005). "Learning by Design: good video games as learning machines." E-Learning, 2(1). pp 5 - 16.

17 September 2009


Presenting information in lectures require careful planning so that the precious class time will not be wasted. Since learning is an interpretative process, new information needs to be integrated with what is already known. deWinstanley and Bjork suggested 5 processes that affect much on how students learn. Attention - divided attention is most detrimental during encoding of new information. What is worse is that "divided attention during a lecture may leave students with a subsequent sense of familiarity ... without the concomitant ability to recall or recognize the material on a direct test of memory". Interpretation and Elaboration - learning requires accurate interpretation and thorough elaboration. Students need to know the "story" behind the new information. Simply presenting a graph or a formula does not help the students to learn why and how the new information can be used. Generation and Retrieval Practice - students learn better if they generate the information rather than just passively absorb information. If students are asked to retrieve information, it is more likely they will recall the information later. Students can create concept maps / reflective blogs / contribute to discussion forums as means of generating the information they have learned.

Other techniques that can promote long term retention of information in the lectures include: spacing - distributing rather than massing the presentations of information at the same time, (an example of spacing is the spiral curriculum, i.e. start with an introduction, then drill down into the topics in the next interaction, and then focusing more details in further iterations), presenting material from more than one standpoint, providing outline (but not too much detail), having students to generate their outline, using visual images and other mnemonic devices, analogies, humor, having the students to make predictions and elaborate interrogation.

To keep student attention, one can also use appropriate games, toys, simulators, play, etc. Interactivity is important to engage students. Pollard and Duvall suggested also using prizes, games, good competition, creating artwork, media, acting out (algorithms), and even rewarding students with stickers and smileys on their papers.

Getting students to generate / reproduce information is a powerful tool. Invention activities are one way to get students attempt the solution and then apply the concept to another area.

Hichens and Lister noted that students expect the teachers to go beyond what is written in the lecture notes, and the teachers to assess student learning during the lectures and adjust the teaching accordingly. Reading straight out from the lecture slides, or making them feel bad / lazy, and going over material too fast / too slow are absolute no no's!


deWinstanley, Patricia Ann and Bjork, Robert, A. (2002). Successful Lecturing: Presenting Information in Ways That Engage Effective Processing. New Directions for Teaching and Learning. No. 89, pp 19- 31.

Hitchens, Michael and Lister, Raymond. (January 2009). A Focus Group Study of Student Attitudes to Lectures. Eleventh Australian Computing Education Conference.

Pollard, Shannon and Duvall, Robert. (2006). Everything I Needed to Know About Teaching I Learned in Kindergarten: Bringing Elementary Education Techniques to Undergraduate Computer Science Classes. SIGCSE 2006. Pp 224 - 228.

03 September 2009

Knowledge Transfer

Most educators are hopeful that their students are able to apply what they have learned in different settings, "from one problem to another within a course, from one course to another, from one school year to the next, and from their years in school to their years in the workplace." (Bransford and Schwartz, 1999). However, researchers have found that people seem to learn things that are very specific (Thorndike and Woodworth, 1901). Further studies have shown that sufficient initial learning is critical in effective transfer, and that concrete examples can enhance initial learning because students see the relevance of new information. But overly contextualized information can impede transfer because information is too tied to the context.

People also forget information easily ("replicative knowing") and people have difficulty applying their knowledge to solve new problems ("applicative knowing") (Broudy, 1977). That is people have difficulty knowing "that" (replicative), and knowing "how" (applicative). What seems to help is people know "with" other concepts / experiences. This is related to Piaget's learning theory of assimilation and accommodation.

Contrasting cases are especially useful for people to "learn with" their experiences. The differences among the contrasting cases help people to notice the pattern that persist among the cases. After the students have a chance to work through some contrasting cases, a lecture that follows results in much greater retention than simply working through the contrasting cases only or have the students summarize what they learned after a lecture.

In order for students to transfer their knowledge from one area to another, they need to "let go" of previously held ideas and behaviors. It is not the same as repeating the same idea / behavior in a new situation. The word "insight", coined by Land, inventor of the Polaroid Land camera, highlights the importance of "letting go" of previous assumptions and strategies rather than simply repeating them (Land, 1982). For Land, insight is "the sudden cessation of stupidity". It is not enough to try to adapt old ideas to new situations. Thus, effective learners revise and actively control their learning when things do not work.

Knowledge transfer also benefits from actively seeking others' ideas and perspectives. Other essential ingredients include: tolerance for ambiguity, courage spans, persistence in the face of difficulty, willingness to learn from others, and sensitivity to the expectations of others. All these help people to be life long learners.

How can students learn to develop these characteristics? Bransford Schwartz suggested lived experiences (spending time in a different country), learning to play a musical instrument, learning to perform on stage, learning to participate in organized sports activities. Learners need to self evaluate in areas such as their commitment to excellence, their need to be in the limelight, their respect for others, their own fears and strategies that may be hampering their progress. Such meta-cognitive reflection are part of "knowing with" new information.

Having students evaluate their own confidence level and then realizing whether their confidence level matches their competence helps them realize whether they are ready to move on to more challenging problems or new problems, or whether they should seek help before they can attempt the problems. Some learners need to know the dangers of confidence when there is little competence. All these prepare the learners to transfer their knowledge to new situations and domain areas.


Bransford, J. and Schwartz, D. (1999). Rethinking Transfer: A Simple Proposal with Multiple Implications. Review of Research in Education, Vol 24, pp 61-100.

Broudy, H.S. (1977). Types of knowledge and purposes of education. In R.C. Anderson, R.J. Spiro and W.E. Montague (Eds.), Schooling and the acquisition of knowledge (pp. 1-17), Hillsdale, NJ: Erlbaum.

Land, E.H. (1982). Creativity and the ideal framework. in G.I. Nierenberg (Ed.), The Art of Creative Thining. New York: Simon & Schuster.

Thorndike, E. L., and Woodworth, R.S. (1901). The infludence of improvement in one mental function upon the efficacy of other functions. Psychological Review, 8, 247-261.