Automation and schema acquisition in learning elementary computer programming: Implications for the design of practice

Two complementary processes may be distinguished in learning a complex cognitive skill such as computer programming. First, automation offers task-specific procedures that may directly control programming behavior, second, schema acquisition offers cognitive structures that provide analogies in new problem situations. The goal of this paper is to explore what the nature of these processes can teach us for a more effective design of practice. The authors argue that conventional training strategies in elementary programming provide little guidance to the learner and offer little opportunities for mindful abstraction, which results in suboptimal automation and schema acquisition. Practice is considered to be most beneficial to learning outcomes and transfer under strict conditions, in particular, a heavy emphasis on the use of worked examples during practice and the assignment of programming tasks that demand mindful abstraction from these examples

Plan-based delivery composition in intelligent tutoring systems for introductory computer programming

In a shell system for the generation of intelligent tutoring systems, the instructional model that one applies should be variable independent of the content of instruction. In this article, a taxonomy of content elements is presented in order to define a relatively content-independent instructional planner for introductory programming ITS's; the taxonomy is based on the concepts of programming goals and programming plans. Deliveries may be composed by the instantiation of delivery templates with the content elements. Examples from two different instructional models illustrate the flexibility of this approach. All content in the examples is taken from a course in COMAL-80 turtle graphics

Instructional strategies and tactics for the design of introductory computer programming courses in high school

This article offers an examination of instructional strategies and tactics for the design of introductory computer programming courses in high school. We distinguish the Expert, Spiral and Reading approach as groups of instructional strategies that mainly differ in their general design plan to control students' processing load. In order, they emphasize topdown program design, incremental learning, and program modification and amplification. In contrast, tactics are specific design plans that prescribe methods to reach desired learning outcomes under given circumstances. Based on ACT* (Anderson, 1983) and relevant research, we distinguish between declarative and procedural instruction and present six tactics which can be used both to design courses and to evaluate strategies. Three tactics for declarative instruction involve concrete computer models, programming plans and design diagrams; three tactics for procedural instruction involve worked-out examples, practice of basic cognitive skills and task variation. In our evaluation of groups of instructional strategies, the Reading approach has been found to be superior to the Expert and Spiral approaches

Variability of worked examples and transfer of geometrical problem-solving skills : a cognitive-load approach

Four computer-based training strategies for geometrical problem solving in the domain of computer numerically controlled machinery programming were studied with regard to their effects on training performance, transfer performance, and cognitive load. A low- and a high-variability conventional condition, in which conventional practice problems had to be solved (followed by worked examples), were compared with a low- and a high-variability worked condition, in which worked examples had to be studied. Results showed that students who studied worked examples gained most from high-variability examples, invested less time and mental effort in practice, and attained better and less effort-demanding transfer performance than students who first attempted to solve conventional problems and then studied work examples

The Effects of Practice Schedule and Critical Thinking Prompts on Learning and Transfer of a Complex Judgment Task

Helsdingen, A. S., Van Gog, T., & Van Merriënboer, J. J. G. (2011). The effects of practice schedule and critical thinking prompts on learning and transfer of complex judgment task. Journal of Educational Psychology, 103(2), 383-398. doi:10.1037/a0022370Many instructional strategies that appear to improve learners’ performance during training, may not realize adequate post test performance or transfer to a job. And the converse has been found true as well: instructional strategies that appear to slow the learner’s progress during training often lead to better post-training or transfer performance. For example, many studies have shown beneficial effects of random over blocked practice on transfer of learning, even though blocked practice often leads to better performance during the training session. In a 2 x 3 factorial experiment (N = 120) with the factors practice schedule (random, blocked) and critical thinking prompts (before task, after task, none), this study investigates whether this also applies to complex judgement tasks, and whether critical thinking prompts can enhance the effectiveness of particular practice schedules. It is hypothesized that prompts provided after task execution yield best transfer in a random practice schedule, whereas prompts provided before task execution yield best transfer in a blocked schedule. In line with our hypothesis, a blocked schedule led to better performance than random practice during training, but not on the transfer test, where a random schedule was beneficial. The hypothesized interaction effect was also found: critical thinking prompts after task execution significantly benefit transfer performance of participants following a random schedule, and transfer performance following a blocked schedule can be a little enhanced through providing critical thinking prompts before task execution. These results warrant instruction in critical thinking processes to teach complex judgment tasks, using random practice schedules combined with critical thinking prompts provided after task execution

Do Learners Really Know Best? Urban Legends in Education

This article takes a critical look at three pervasive urban legends in education about the nature of learners, learning, and teaching and looks atwhat educational and psychological research has to say about them. The three legends can be seen as variations on one central theme, namely, that it is the learner who knows best and that she or he should be the controlling force in her or his learning. The first legend is one of learners as digital natives who form a generation of students knowing by nature how to learn from new media, and for whom “old” media and methods used in teaching/learning no longer work. The second legend is the widespread belief that learners have specific learning styles and that education should be individualized to the extent that the pedagogy of teaching/learning is matched to the preferred style of the learner. The final legend is that learners ought to be seen as self-educators who should be given maximum control over what they are learning and their learning trajectory. It concludes with a possible reason why these legends have taken hold, are so pervasive, and are so difficult to eradicate