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20th Annual Conference on International Computing Education Research (ICER)

作者： Thorgeirsson, Sverrir Zhang, Chengyu Weidmann, Theo B. Weidmann, Karl-Heinz Su, Zhendong Swiss Fed Inst Technol Zurich Switzerland Univ Appl Sci Vorarlberg Dornbirn Austria

ISBN: (纸本)9798400704758

This paper presents a comparative study of Algot, a visual programming language designed to bridge the syntax-semantics gap via liveness and programming by demonstration, and the textual programming language Python. We conducted an experimental, within-subjects study with 24 undergraduate computer science students who performed recursion-based tasks in each language while their cognitive load was measured using an electroencephalogram and a validated survey instrument. The students received a brief introduction to Algot, but were all familiar with Python. The students performed significantly better when programming in Algot, but the cognitive load levels were similar according to both instruments. Our results provide evidence that within the domain that was tested, Algot can be quickly learned, and that students do not find it more cognitively demanding than working in a familiar language.

关键词： electroencephalography undergraduate education CS1 recursion cognitive load visual programming programming by demonstration direct manipulation live programming

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Explaining Algorithms with the Visual programming Language Algot 29

Explaining Algorithms with the Visual Programming Language A...

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29th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE)

作者： Thorgeirsson, Sverrir Graf, Oliver Swiss Fed Inst Technol Dept Comp Sci Zurich Switzerland

ISBN: (纸本)9798400706035

Algot is a visual, live programming language for computer science education that uses a novel implementation of programming by demonstration. Recent experimental studies indicate that Algot is effective for teaching foundational computer science concepts in secondary and tertiary education. In this proposed ITiCSE session, we will give a brief demonstration of how Algot works and how it can be used to implement algorithms that are typically taught in CS1, such as sorting and searching. Our primary intention is to help practitioners in the ITiCSE audience determine if Algot could be appropriate for their own classrooms.

关键词： visual programming live programming programming by demonstration secondary education tertiary education

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Recursion in Secondary Computer Science Education: A Comparative Study of Visual programming Approaches 2024

Recursion in Secondary Computer Science Education: A Compara...

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55th ACM Technical Symposium on Computer Science Education (SIGCSE)

作者： Thorgeirsson, Sverrir Lais, Lennart C. Weidmann, Theo B. Su, Zhendong Swiss Fed Inst Technol Zurich Switzerland

ISBN: (纸本)9798400704239

While recursion is a fundamental technique in computer programming, it is challenging for novices, for example since it requires tracing non-linear and hierarchical sequences of execution. Though algorithm visualizations and visual programming may be helpful, such tools need to offer sufficiently expressive environments that support active, constructivist learning via exploration and experimentation. In this study, we investigated whether Algot, a visual programming language that relies on a novel programming-by-demonstration paradigm, is effective for teaching recursion to 1417 year old students, and whether it compares favorably to the popular visual programming language Scratch. We conducted an experimental study with 23 participants where they learned recursion in a video tutorial using Algot and Scratch, worked out code exercises in each respective language, and then solved a post-test on recursion. Despite the participants being more familiar with Scratch than Algot, our results indicated that students instructed with Algot demonstrated a significantly better understanding of recursion (Bayes Factor = 14.09, p = 0.005, Cohen's d = 1.30). We also found that students reported a similar level of enjoyment of each language. These findings provide preliminary evidence about the effectiveness of the programming-by-demonstration paradigm, as implemented in Algot, in aiding the comprehension of complex programming concepts like recursion.

关键词： visual programming block-based programming recursion programming by demonstration educational technology secondary education

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MorphIO: Entirely Soft Sensing and Actuation Modules for programming Shape Changes through Tangible Interaction 19

MorphIO: Entirely Soft Sensing and Actuation Modules for Pro...

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ACM Designing Interactive Systems Conference (DIS)

作者： Nakayama, Ryosuke Suzuki, Ryo Nakamaru, Satoshi Niiyama, Ryuma Kawahara, Yoshihiro Kakehi, Yasuaki Keio Univ Keio Japan Univ Colorado Boulder CO 80309 USA Univ Tokyo Tokyo Japan

ISBN: (纸本)9781450358507

We introduce MorphIO, entirely soft sensing and actuation modules for programming by demonstration of soft robots and shape-changing interfaces. MorphIO's hardware consists of a soft pneumatic actuator containing a conductive sponge sensor. This allows both input and output of three-dimensional deformation of a soft material. Leveraging this capability, MorphIO enables a user to record and later playback physical motion of programmable shape-changing materials. In addition, the modular design of MorphIO's unit allows the user to construct various shapes and topologies through magnetic connection. We demonstrate several application scenarios, including tangible character animation, locomotion experiment of a soft robot, and prototyping tools for animated soft objects. Our user study with six participants confirms the benefits of MorphIO, as compared to the existing programming paradigm.

关键词： shape-changing interfaces programming by demonstration soft robots pneumatic actuation tangible interactions

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Solution Authoring via demonstration and Annotation: An Empirical Study 16

Solution Authoring via Demonstration and Annotation: An Empi...

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16th IEEE International Conference on Advanced Learning Technologies (ICALT)

作者： Myers, Karen Gervasio, Melinda SRI Int Ctr Artificial Intelligence Menlo Pk CA 94025 USA

ISBN: (纸本)9781467390415

A major impediment to the widespread deployment of intelligent training systems is the high cost of developing the content that drives their operation. Techniques grounded in end-user programming have shown great promise for reducing the burden of content creation. With these approaches, a domain expert demonstrates a solution to a task, which is then generalized to a broader model. This paper reports on a concept validation study that provides an empirical basis for the design of solution authoring frameworks based on end-user programming techniques. The study shows that non-expert users are comfortable with the approach and are capable of applying it to generate quality solution models. It also identifies constructs that, while important for accurate solution characterization, can lead to confusion and so warrant special care in tool design. Based on these results, we make recommendations for the design of solution-authoring tools in support of automated assessment for tutoring systems.

关键词： automated assessment end user programming programming by demonstration intelligent training systems

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Training agents to recognize text by example

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AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS 2001年第1-2期4卷 79-92页

作者： Lieberman, H Nardi, BA Wright, DJ MIT Media Lab Cambridge MA 02139 USA AT&T Labs W Menlo Park CA USA Apple Comp Inc Cupertino CA 95014 USA

An important function of an agent is to be "on the lookout" for bits of information that are interesting to its user, even if these items appear in the midst of a larger body of unstructured information. But how to tell these agents which patterns are meaningful and what to do with the result? Especially when agents are used to recognize text, they are usually driven by parsers which require input in the form of textual grammar rules. Editing grammars is difficult and error-prone for end users. Grammar ["Grammars by Example"] is the first direct manipulation interface designed to allow nonexpert users to define grammars interactively. The user presents concrete examples of text that he or she would like the agent to recognize. Rules are constructed by an iterative process, where Grammex heuristically parses the example, displays a set of hypotheses, and the user critiques the system's suggestions. Actions to take upon recognition are also demonstrated by example.

关键词： agents parsers grammars programming by example programming by demonstration

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Why tutored problem solving may be better than example study: Theoretical implications from a simulated-student study

Why tutored problem solving may be better than example study...

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9th International Conference on Intelligent Tutoring Systems

作者： Matsuda, Noboru Cohen, William W. Sewall, Jonathan Lacerda, Gustavo Koedinger, Kenneth R. Carnegie Mellon Univ Human Comp Interact Inst Pittsburgh PA 15213 USA Carnegie Mellon Univ Machine Learning Dept Pittsburgh PA 15213 USA

ISBN: (纸本)9783540691303

Is learning by solving problems better than learning from worked-out examples? Using a machine-learning program that learns cognitive skills from examples, we have conducted a study to compare three learning strategies: learning by solving problems with feedback and hints from a tutor, learning by generalizing worked-out examples exhaustively, and learning by generalizing worked-out examples only for the skills that need to be generalized. The results showed that learning by tutored problem solving outperformed other learning strategies. The advantage of tutored problem solving was mostly due to the error detection and correction that was available only when skills were applied incorrectly. The Current study also suggested that learning certain kinds of conditions to apply rules only for appropriate Situations is quite difficult.

关键词： intelligent authoring system simulated student programming by demonstration machine learning Cognitive Tutor

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Comparing Cognitive Load Among Undergraduate Students programming in Python and the Visual Language Algot 2024

Comparing Cognitive Load Among Undergraduate Students Progra...

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55th ACM Technical Symposium on Computer Science Education (SIGCSE)

作者： Thorgeirsson, Sverrir Weidmann, Theo B. Weidmann, Karl-Heinz Su, Zhendong Swiss Fed Inst Technol Zurich Switzerland Univ Appl Sci Vorarlberg Dornbirn Austria

ISBN: (纸本)9798400704239

This paper examines whether undergraduate students perform better and experience lower cognitive load when programming in Algot, a visual programming language that supports programming by demonstration, than in the textual programming language Python. We recruited 38 first-semester computer science university students who had received prior instruction in the programming language Python but were unfamiliar with Algot. Participants reviewed a 12-minute video tutorial about Algot and performed the same programming tasks in Python and Algot. We graded student submissions, estimated cognitive load through physiological measures and a validated post-test survey, and evaluated free-form feedback. Our results indicated that students experienced lower negative (extraneous and intrinsic) and higher positive (germane) cognitive load when programming in Algot. Additionally, students programming in Algot scored an average grade of 5.8 out of 10, compared to an average grade of 3.4 when using Python for the same tasks, and according to the free-form feedback, Algot is perceived as well-designed and easy to learn.

关键词： visual programming programming by demonstration undergraduate education algorithms and data structures cognitive load

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Teaching and learning of robot tasks via observation of human performance

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ROBOTICS AND AUTONOMOUS SYSTEMS 2004年第2-3期47卷 109-116页

作者： Dillmann, R Univ Karlsruhe TH Inst Comp Design & Fault Tolerance D-76128 Karlsruhe Germany

Within this paper, an approach for teaching a humanoid robot is presented that will enable the robot to team typical tasks required in everyday household environments. Our approach, called programming by demonstration, which is implemented and successfully used in our institute to teach a robot system is presented. Firstly, we concentrate on an analysis of human actions and action sequences that can be identified when watching a human demonstrator. Secondly, sensor aid systems are introduced which augment the robot's perception capabilities while watching a human's demonstration and the robot's execution of tasks respectively. The main focus is then layed on the knowledge representation in order to be able to abstract the problem solution strategies and to transfer them onto the robot system. (C) 2004 Elsevier B.V. All rights reserved.

关键词： robot tasks programming by demonstration one-shot-leaming

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Predicting Students' Performance with SimStudent: Learning Cognitive Skills from Observation 13

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13th International Conference on Artificial Intelligence in Education (AIED 2007)

作者： Matsuda, Noboru Cohen, William W. Sewall, Jonathan Lacerda, Gustavo Koedinger, Kenneth R. Carnegie Mellon Univ Human Comp Interact Inst Pittsburgh PA 15213 USA

ISBN: (纸本)9781586037642

SimStudent is a machine-learning agent that learns cognitive skills by demonstration. SimStudent was originally built as a building block for Cognitive Tutor Authoring Tools to help an author build a cognitive model without significant programming. In this paper, we evaluate a second use of SimStudent, viz., student modeling for Intelligent Tutoring Systems. The basic idea is to have SimStudent observe human students solving problems. It then creates a cognitive model that can replicate the students' performance. If the model is accurate, it would predict the human students' performance on novel problems. An evaluation study showed that when trained on 15 problems, SimStudent accurately predicted the human students' correct behavior on the novel problems more than 80% of the time. However, the current implementation of SimStudent does not accurately predict when the human students make errors.

关键词： Cognitive modeling programming by demonstration inductive logic programming Cognitive Tutor intelligent authoring

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