- Here’s a post at IGN about the use of videogames in education.
- Abdulaziz Ghuloum has written a tutorial about writing your own compiler. The difference is that it is a progressive tutorial rather than incremental. You don’t have to wait until the end before you can actually try the compiler out.
Richard Hake, one of the creators of the well-known Force Concept Inventory for assessing physics understanding, posts a lot of very informative material to the physlrnr, phys-l, and math-teach lists. Lately there was a re-hash again over a research article by Klahr & Nigem about direct instruction vs. discovery learning. In a typical unfairly designed psych experiment, Klahr compared direct instruction to a group in which students were left to fend completely on their own (unguided discovery). Students fared better in the direct instruction condition (although actually they had a discovery activity before the instruction began as well). People in the government and people who favor traditional schooling approaches jumped on that article as proof that direct instruction is best.
Here is Hake’s response to it from back in 2004. See the archives of the above lists for more recent discussions. I would also add some other references that counter the mis-interpretation of Klahr’s study, and clarify when and how direct instruction can be useful. There is an article entitled “A time for telling” from 1998 by John Bransford in the journal Cognition & Instruction. Also another 1991 article showed that giving students a discovery-learning experience before a lecture made for much better learning gains:
Brant, G., Hooper, E., & Sugrue, B. (1991). Which comes first: The simulation or the lecture? Journal of Educational Computing Research, 7(4), 469-481.
Here’s a related paragraph from a review I wrote a few years ago:
Simulation before instruction. A number of studies have found advantages to using simulations in sequence with other forms of instruction such as a lecture, but not necessarily during a lecture as earlier examples demonstrated (Thomas & Hooper, 1991). This makes sense when again realizing that simulations are environments that do not provide information to students so much as they require information from students to be used effectively. Particularly effective is allowing students to use a simulation before a lecture or other activity (Brant, Hooper, & Sugrue, 1991). Even though students may or may not fully understand the model underlying the simulation they use, after exploring the environment they may have formed questions or strategies for learning about the domain. So even when a simulation is not completely understandable to a student, it may engender a preparedness for future learning, and the students may attend differently to a subsequent lecture or other learning activity.
Here are some more general paragraphs from earlier in the review:
In a large-scale analysis of mathematics classrooms, Harold Wenglinsky found higher student achievement in classrooms using computers for simulation and data exploration activities. In contrast, achievement scores actually declined by six tenths of a year in eighth-grade classrooms in which computers were used for decontextualized drill activities instead of simulations (Wenglinsky, 1998).
Students learn more than just facts when using computer simulations. Njoo and de Jong (1993) have found that the educational benefits of simulations are revealed more in tests of intuitive knowledge, such as reasoning about “what if” scenarios, rather than tests of more factual knowledge. Similarly, Thomas and Hooper (1991) concluded in a review of research that the use of simulations is more effective when the educational goal is for students to transfer and apply knowledge to real-world problems rather than memorize facts or procedures. This is not as surprising when considering that the primary design principle of simulations, fidelity, is designed to lower the amount of work needed to transfer one’s knowledge to the actual system it is modeling.