Developing and Researching PhET simulations for Teaching Quantum Mechanics

Quantum mechanics is difficult to learn because it is counterintuitive, hard to visualize, mathematically challenging, and abstract. The Physics Education Technology (PhET) Project, known for its interactive computer simulations for teaching and learning physics, now includes 18 simulations on quantum mechanics designed to improve learning of this difficult subject. Our simulations include several key features to help students build mental models and intuitions about quantum mechanics: visual representations of abstract concepts and microscopic processes that cannot be directly observed, interactive environments that directly couple students' actions to animations, connections to everyday life, and efficient calculations so students can focus on the concepts rather than the math. Like all PhET simulations, these are developed using the results of education research and feedback from educators, and are tested in student interviews and classroom studies. This article provides an overview of the PhET quantum simulations and their development. We also describe research demonstrating their effectiveness and share some insights about student thinking that we have gained from our research on quantum simulations.Comment: accepted by American Journal of Physics; v2 includes an additional study, more explanation of research behind claims, clearer wording, and more reference

TEACHING ENGLISH AS A FOREIGN LANGUAGE IN VOCATIONAL HIGH SCHOOL USING CONSTRUCTIVISM APPROACH

Constructivism approach is the newest way to teach Language as foreign language. Mostly, many Vocational high schools in Indonesia use behaviorist approach which the students have to say what the teacher says and what the book says. The problems are; is the method appropriate? Is it works effectively or not? Does it give some benefits for the students or will become the parts of his life? These questions must be considered to achieve success in language acquisition not only as something that is accomplished in the classroom during the particular course, but also as a life-long activity, considering the graduates of Vocational high school students are prepared for the business world . This paper attempts to give a scratch of constructivism approach in teaching English as foreign language which might be a great necessity for the teacher of vocational high school. The content also involves Curriculum in order to be accuracy with the materials. Several points should be taken into consideration to apply the best method in classroom teaching

Engineering News, Fall 2019

https://scholarcommons.scu.edu/eng_news/1043/thumbnail.jp

Impacts of directed tutorial activities in computer conferencing: a case study

This paper describes a qualitative study of asynchronous electronic conferencing by three tutorial groups on the same postgraduate course (Teaching English to Speakers of Other Languages Worldwide), forming part of an MA in Applied Linguistics (via Distance Education) at the Open University, UK. The groups varied in the degree to which the tutor participated in the discussion and in whether the tutor's input took the form of responding to student posts or the setting of tasks to scaffold the learners' development of academic skills. It is argued that the least interventionist strategy in terms of tutor response and task-setting resulted in the least productive conference discussion in terms of both communicative interaction and academic development, while a more interventionist role by the tutor depended for its success on characteristics of the tutor input and the task set

A Deeper Look at Student Learning of Quantum Mechanics: the Case of Tunneling

We report on a large-scale study of student learning of quantum tunneling in 4 traditional and 4 transformed modern physics courses. In the transformed courses, which were designed to address student difficulties found in previous research, students still struggle with many of the same issues found in other courses. However, the reasons for these difficulties are more subtle, and many new issues are brought to the surface. By explicitly addressing how to build models of wave functions and energy and how to relate these models to real physical systems, we have opened up a floodgate of deep and difficult questions as students struggle to make sense of these models. We conclude that the difficulties found in previous research are the tip of the iceberg, and the real issue at the heart of student difficulties in learning quantum tunneling is the struggle to build the complex models that are implicit in experts' understanding but often not explicitly addressed in instruction.Comment: v2, v3 updated with more detailed analysis of data and discussion; submitted to Phys. Rev. ST: PE

The Mechanics of Embodiment: A Dialogue on Embodiment and Computational Modeling

Embodied theories are increasingly challenging traditional views of cognition by arguing that conceptual representations that constitute our knowledge are grounded in sensory and motor experiences, and processed at this sensorimotor level, rather than being represented and processed abstractly in an amodal conceptual system. Given the established empirical foundation, and the relatively underspecified theories to date, many researchers are extremely interested in embodied cognition but are clamouring for more mechanistic implementations. What is needed at this stage is a push toward explicit computational models that implement sensory-motor grounding as intrinsic to cognitive processes. In this article, six authors from varying backgrounds and approaches address issues concerning the construction of embodied computational models, and illustrate what they view as the critical current and next steps toward mechanistic theories of embodiment. The first part has the form of a dialogue between two fictional characters: Ernest, the �experimenter�, and Mary, the �computational modeller�. The dialogue consists of an interactive sequence of questions, requests for clarification, challenges, and (tentative) answers, and touches the most important aspects of grounded theories that should inform computational modeling and, conversely, the impact that computational modeling could have on embodied theories. The second part of the article discusses the most important open challenges for embodied computational modelling

THE CHARACTERISTICS OF BANYUMASAN CONVERSATIONAL IMPLICATURES

To mean what you say is sometimes problematic in daily conversation, moreover in some indigenous dialects. It requires comprehensive context to achieve the core of communication. So does in Banyumasan. Banyumasan or Banyumas dialect is a variant which is found along the flow of Serayu river. The river flows from Sindoro-Sumbing Mountains (Koentjaraningrat, 1984:23). Banyumas dialect is one of some variants of Javanese language. Banyumasan has some differences compared to standard Javanese spoken in Jogjakarta, Surakarta and Semarang. Those differences are also reflected in the characteristics of conversational implicatures found in this dialect. Conversational implicaure is a proposition that is implied by the utterance of sentence in a context even though that proposition is not a part of nor an entailment of what was actually said (Grice, 1975; Gazdar, 1979). The characteristics of conversational implicatures are calculability, cancellability, non-detachability, non-conventionality, and indeterminacy. (Grice, 1975; Levinson, 1983; Thomas, 1996; dan Cruse, 2004). A dialect has different characteristics compared to other dialects of the same language and so does the characteristic o

Deep Clustering and Conventional Networks for Music Separation: Stronger Together

Deep clustering is the first method to handle general audio separation scenarios with multiple sources of the same type and an arbitrary number of sources, performing impressively in speaker-independent speech separation tasks. However, little is known about its effectiveness in other challenging situations such as music source separation. Contrary to conventional networks that directly estimate the source signals, deep clustering generates an embedding for each time-frequency bin, and separates sources by clustering the bins in the embedding space. We show that deep clustering outperforms conventional networks on a singing voice separation task, in both matched and mismatched conditions, even though conventional networks have the advantage of end-to-end training for best signal approximation, presumably because its more flexible objective engenders better regularization. Since the strengths of deep clustering and conventional network architectures appear complementary, we explore combining them in a single hybrid network trained via an approach akin to multi-task learning. Remarkably, the combination significantly outperforms either of its components.Comment: Published in ICASSP 201