Oldal 86 [86]
OCR
9.2 STUDENT-ORCHESTRATED COMPUTER ALGORITHMS 85 — Naps, Eagan, and Norton (2000) also reported anecdotal success with the incorporation of stop-and-think guestions into their AV system. They found that forcing students to answer the guestions, registering their responses for grading purposes, and giving them immediate feedback could result in more effective learning. — On the other hand, Jarc, Feldman, and Heller (2000) reported opposite results. The AV system they developed presents students with algorithm animations in two modes: (1) “Show Me” (students passively watch the animation, trying to learn the behaviour of the studied algorithm); (2) “Tll Try” (Students are engaged with interactive prediction questions). Surprisingly, the group that used the interactive prediction feature of the AV system performed worse (but not significantly) than the group that did not use it. Possible enhancing/diminishing factors contributing to the above results are: — The immediate feedback that students receive after they have answered the questions can reset confused ones’ perception of the algorithm back to the track intended by the teacher (Naps et al., 2000). — Instead of thinking thoroughly on the questions, students (especially weaker ones) may tend to view interactive prediction as a guessing game (Jarc et al., 2000). In the following paragraphs, we analyse further factors that could increase/ diminish the effectiveness of AV systems that include interactive prediction. 9.2 Student-orchestrated computer algorithms A special case of interactive prediction is when students have to orchestrate the studied algorithm. They are invited to predict and even “perform” (for a given input; using an interactive visual learning environment) the entire step sequence of the algorithm. Features like immediate feedback, possibility to try again, and help button (available at each step of the algorithm) can guarantee that all students will be able to complete their task. The primary goal of the orchestrating process is not to assess but to enhance or refine students’ understanding about the studied algorithm. Obviously, this “You Are in Charge” phase of the learning process should be preceded by “Preparation” phases (teacher explanation; watching the animated algorithm), when students are initiated into and familiarized with the strategy the algorithm is built on. A possible scenario could be: “Listen to It” (to be initiated into) + “Watch It” (to become familiar with) + “Try It” (to assimilate it). In such learning environments (especially during “Try It” phases), users become active players of the AV process. If an AV system has this feature, then the concept of epistemic fidelity acquires new connotations. “Not blind users”
