Autobiographical retrieval has been modeled as a predictive retrieval process, in which strategies elaborate the original retrieval cue relying on information accessed in knowledge structures to direct the search. Previous studies have demonstrated that event concepts differ in their utility in this process. The present study examines the type of information made available by accessing two such event concepts, activities and general actions. Activity structures are shown to enable more concrete predictions about included objects, people, and setting information, while general actions tend to be associated with internal mental states. These differences in available features are consistent with previously observed retrieval time differences between these types of concepts and support a general underlying mechanism of predictive inferencing in retrieval. The results suggest the types of information that computer models of memory organization should utilize in their representations of event structures and the reasoning mechanisms that depend on those structures.

In this paper we describe two properties of most psychological and AI models of scientific problem solving: they are one-peiss, and feed forward. W e then discuss the results of an experiment which suggests that experts use problem solving representations more flexibly than these models suggest. W e introduce the concept of incremental envisioning to account for this flexible behavior. Finally, we discuss the implications of this work for psychological models of scientific problem solving and for AI programs which solve problems in scientific domains.

An important component of problem solving is the ability to make use of previous examples.This requires noticing the relevance between the current and previous problems. W e examine the role of the superficial and structural relations among problems and the remindings that these similarities elicit in a problem solving situation. Students learned to program in an electronic book environment in which they were able to store and later retrieve solved problems. Their use of jM-evious solutions suggests that novices are indeed sensitive to structural similarities and can use retrieved solutions in new problem situations.

In many domains, novices exhibit a bias in the direction in which they reason about problems. Earlier studies of LISP programmers using a graphical representation suggested that novice LISP programmers tend to reason forward, working from initial input data toward the goal. W e examined novice programmers learning LISP using the GIL programming tutor and manipulated the direction subjects were allowed to reason (forward, backward, or free). Subjects who were required to work backwards (from goal toward givens) exhibited more difficulty solving the problems than subjects working forward or subjects left free to chose their direction. Backward subjects required more time to solve problems, made more errors, and required more time to plan each solution. W e suggest that these effects and preferences occur because forward reasoning is more congruent with the way novices reason about computer programs, resulting in an increased working memory load for subjects required to work backward.

Novices often experience great difficulty leeirning new domains. Thus, understanding how best to scaffold novice problem solving has potentiaUy tremendous importance for learning in formal domains. In this paper, we present results from ein experimental study that compared learning outcomes of students solving introductory programming problems in three different learning environments. This range of environments v£iries in two ways. First, the notations used in the environments vary between diagrammatic and textuaJ. More importantly, the environments differ in the cognitive activities students are led to perform while solving problems, such as prediction of intermediate results and noting future goals to achieve. This experiment demonstrated that environments that scaffold more of the important cognitive activities lead to superior performance, regardless of whether the environments are textual or diagrammatic.

There is little doubt that examples play a major role in acquiring a n e w skill. H o w examples improve learning, however, is subject to some debate. Re- cently, two different classes of theories have been pro- posed to explain w h y examples are such an effective manner of learning. Example Generalization m o d - els suggest that problem solving rules are acquired while studying examples. Knowledge Compilation models, on the other hand, suggest that examples are useful because they guide future problem solv- ing, where the necessary rules are created. Consis- tent with knowledge compilation models, w e found that separating target problems from source exam- ples hindered learning because the source exeimples could not be remembered to guide problem solving. W e also found that if sources are not accessible or re- m e m b e r e d during problem solving, learning occurs best w h e n the sources are problems to be solved, rather than examples. Taken together, these results provide strong support for the knowledge compilation view: in order for an example to be most effective, the knowledge gained from the example must be ap- plied to solving a new problem.

Variation in second language acquisition is evident from earliest stages. This study examined effects of learning tasks (retrieval practice, comprehension, verbal repetition) on comprehension of Turkish as a new language. Undergraduates (N = 156) engaged with Turkish spoken dialogues in a computer-assisted language learning session via Zoom, with learning tasks manipulated between-subjects. Participants completed pre/posttests assessing comprehension of Turkish number and case marking, a vocabulary test, and open-response questions gauging explicit awareness. The retrieval-practice group showed highest performance overall, after controlling for significant effects of nonverbal ability and pretest. For comprehension of number/case marking, the comprehension group performed comparably to the retrieval-practice group. For vocabulary comprehension, the verbal-repetition group performed comparably to the retrieval-practice group. Differential performance associated with learning tasks indicates benefits of testing and production and aligns with transfer-appropriate processing. As predicted by the noticing hypothesis, explicit awareness of number and case marking correlated with comprehension accuracy.