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Research has identified 10 high-leverage teaching practices (HLTPs) that can impact student learning of a foreign language. While acknowledging the importance of this work, more research is needed to inform the preparation of novice teachers to enact these practices. In response, the researchers conducted a case study involving two foreign language teacher preparation programs in the United States and Germany, to better understand how the two very different programs prepare their candidates to implement HLTPs, which HLTPs are emphasized, and how successful they are at preparing their aspiring teachers to implement one practice that has been identified in the research as particularly important (facilitating target language comprehensibility). Survey, teaching observation, and interview data collected from teacher candidates and their instructors suggested the critical nature of select HLTPs, that some of the subcomponents of one of these practices may be more challenging for novice teachers to master than others, and that there may be multiple approaches to preparing foreign language teachers to implement HLTPs.
This volume is largely about nontraditional data; this paper is about a nontraditional visualization: classification trees. Using trees with data will be new to many students, so rather than beginning with a computer algorithm that produces optimal trees, we suggest that students first construct their own trees, one node at a time, to explore how they work, and how well. This build-it-yourself process is more transparent than using algorithms such as CART; we believe it will help students not only understand the fundamentals of trees, but also better understand tree-building algorithms when they do encounter them. And because classification is an important task in machine learning, a good foundation in trees can prepare students to better understand that emerging and important field. We also describe a free online tool—Arbor—that students can use to do this, and note some implications for instruction.
The notion of “bounded rationality” was introduced by Simon as an appropriate framework for explaining how agents reason and make decisions in accordance with their computational limitations and the characteristics of the environments in which they exist (seen metaphorically as two complementary scissor blades).We elaborate on how bounded rationality is usually conceived in psychology and on its relationship with logic. We focus on the relationship between heuristics and some non-monotonic logical systems. These two categories of cognitive tools share fundamental features. As a step further, we show that in some cases heuristics themselves can be formalized from this logic perspective. We have therefore two main aims: on the one hand, to demonstrate the relationship between the bounded rationality programme and logic, understood in a broad sense; on the other hand, to provide logical tools of analysis of already known heuristics. This may lead to results such as the characterization of fast and frugal binary trees in terms of their associated logic program here provided.
Since students’ knowledge of scientific language can be one of the main difficulties when learning science, teachers must have adequate knowledge of scientific language as well as the teaching and learning of it. Currently, little is known about teachers’ practices and, thus, teachers’ knowledge of scientific language, in general, and the teaching and learning of it (Pedagogical Scientific Language Knowledge, PSLK) in particular. For this reason, with this systematic review, we seek to identify elements of pre- and in-service primary and secondary science teachers’ PSLK. The search was conducted on the database Education Resources Information Center (ERIC) and resulted in 35 articles with empirical evidence after the selection process. The results have been deductively and inductively categorized following the framework of the Refined Consensus Model of Pedagogical Content Knowledge, elaborating elements of different knowledge categories that shape PSLK, as well as PSLK itself (e.g., knowledge of (i) scientific language role models, (ii) making scientific terms and language explicit, (iii) providing a discursive classroom, and (iv) providing multiple representations and resources). We can conclude that more research on PSLK is needed as analyzed articles are mainly based on case studies. Additionally, this paper shows a need for a stronger focus on scientific language in teacher education programs. Implications for further research and teacher education are discussed.
We investigated retrieval-induced forgetting of motor sequences in samples of Chinese participants. Retrieval-induced forgetting occurs when selective retrieval of a subset of information stored in memory causes forgetting for the non-retrieved rest. This phenomenon critically depends on the organised storage of separate categories of memory representations. In studies with participants from a Western culture (Germany), a categorization in left- and right-hand movements previously had been supported by letter stimuli based on a spatial mental representation of the Roman alphabet. The same assignment of letters from the beginning or end of the alphabet to motor sequences performed either with the left- or the right-hand did not entail retrieval-induced forgetting in the present study, however (Experiment 1). In Experiment 2, visual features of displaying to-be-learned sequences additionally supported a distinction into left and right. In Experiment 3, learning trials provided verbal category labels. The occurrence of retrieval-induced forgetting in the latter two experiments suggests language-dependent organisation of non-verbal items in memory.
We investigated whether retrieval-based learning can facilitate the acquisition of cognitive skills, focusing on the control-of-variables strategy. This core scientific experimentation skill is regularly taught in science education classes because understanding it is essential for understanding experimental investigations in science. In the present study, participants initially read a text explaining the control-of-variables strategy. We compared the effects of subsequent retrieval practice and restudy of the text in performing a transfer test requiring the application of the control-of-variables strategy by judging the validity of a number of experimental designs. In addition, recall of the initially studied text was assessed as well. Repeated retrieval practice in combination with restudy opportunities resulted in better performance in both the transfer test and the recall test as compared to mere restudy or a single study opportunity. These findings demonstrate that retrieval practice is a useful tool for promoting deep conceptual learning.
The effect of direct instruction and web quest on learning outcome in computer science education.
(2018)
Answers to the questions of which instructional methods are suitable for school and should be applied in teaching individual subjects and also how instructional methods support the act of learning represent challenges to general education and education in individual subjects. This study focuses on the empirical examination of learning outcome with respect to two instructional methods: direct instruction and web quest. An SPF-2 × 2•2 design is used to control instructional method, time and class context. Learning outcome on QR code is assessed with reference to multiple-choice test items. The empirical findings show that learning with direct instruction performs better than web quest.
cpm.4.CSE/IRT (compact process model for Competence Science Education based on IRT models) is a process model for competence measurement based on IRT models. It allows the efficient development of measuring instruments for computer science education. Cpm.4.CSE/IRT consists of four sub processes: B1 determine items, B2 test items, B3 analyze items according to Rasch model, and B4 interpret items by criteria. Cpm.4.CSE/IRT is modeled in IDEF0, a process modeling language that is standardized and widely used. It is implemented in R, an open-source software optimized for statistical calculations and graphics that allows users to interact using the web application framework Shiny. Through coordinated processes, cpm.4.CSE/IRT ensures the quality and comparability of test instruments in competence measurement. Cpm.4.CSE/IRT is demonstrated using an example from the competence area of Modeling.
Gamification and game-based learning have been established as powerful tools in education. Location-based games (geogames) have been established following mainly a ‘seek-and-find’ game-mechanic, challenging mechanics like simulations are rarely used. We describe an approach for creating an educational location-based game (geogame). The central design problem consists in integrating an ecological simulation into the location-based game flow. We show how to combine these two game mechanics by simplifying complex simulations while maintaining their validity. In an empirical study we evaluate our geogame with secondary school students (N = 329). Our quasi-experimental pre-post-test design focuses on the game-related enjoyment provided by a simplified simulation task within a geogame compared to a more complex desktop simulation and to a geogame without simulation. The results show that the players of the Geogame spend much less time on interacting with the simulation than on other tasks. Nevertheless, the simulation within the geogame contributes positively to the game playing experience. Player enjoyment is even found to be slightly higher in the simulation geogame than in the indoor simulation. A critical threshold of time for using simulations within location-based game mechanics is discussed and related design-pattern for geogames are presented to support educators and game developers in the co-design of challenging location-based games. This study contributes to locate ecological simulations in areas where they actually take place. Complex topics and competencies in education become “real” for players in an outdoor experience.