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5th International Conference on learning with MOOCs, LWMOOCS 2018

作者： Demetriadis, Stavros Tegos, Stergios Psathas, Georgios Tsiatsos, Thrasyvoulos Weinberger, Armin Caballe, Santi Dimitriadis, Yannis Sanchez, Eduardo Gomez Papadopoulos, Pantelis M. Karakostas, Anastasios Aristotle University School of Informatics Thessaloniki Greece Department of Educational Technology Saarland University Saarbriicken Germany Faculty of Computer Science Multimedia and Telecommunications Universitat Oberta de Catalunya Barcelona Spain Universidad de Valladolid School of Telecommunications Engineering Valladolid Spain Aarhus University Centre for Teaching Development and Digital Media Aarhus Denmark Center for Research and Technology - Hellas Information Technologies Institute Thessaloniki Greece

ISBN: (纸本)9781538665336

This paper presents the colMOOC project perspective for integrating a conversational agent service in Massive Open Online Courses (MOOCs) to facilitate peer dialogue during chat-based activities. Furthermore, it provides high level system architecture to highlight key aspects of the technology infrastructure and the functionality of the software system. The rationale of the approach follows the tenets of several converging theoretical perspectives emphasizing the value of learners' dialogue and constructive argumentation as knowledge building processes during collaborative activities. The MOOC teacher (domain expert) is expected to play a key role by entering in the system conceptual links that guide the agent to make relevant questioning interventions. Thus, the agent tool is mediating group-teacher interactions in a MOOC environment aiming to increase the transactive quality of peer dialogue. The paper discusses also the 'Academically Productive Talk' model that provides the basis for the agent interventions and the major software components of the system, including the colMOOC Editor and the colMOOC Player. © 2018 IEEE.

关键词： computer aided instruction

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An Empirical Study of Super-resolution on Low-resolution Micro-expression Recognition

arXiv

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arXiv 2023年

作者： Zhou, Ling Wang, Mingpei Huang, Xiaohua Zheng, Wenming Mao, Qirong Zhao, Guoying The School of Computer Science and Engineering Macau University of Science and Technology China The Key Laboratory of Child Development and Learning Science Ministry of Education Southeast University Nanjing210096 China School of Computer Engineering Nanjing Institute of Technology Jiangsu China The School of Biological Science and Medical Engineering Southeast University Jiangsu Nanjing210096 China The School of Computer Science and Communication Engineering Jiangsu University Jiangsu Zhenjiang China The Center for Machine Vision and Signal Analysis University of Oulu Finland

Micro-expression recognition (MER) in low-resolution (LR) scenarios presents an important and complex challenge, particularly for practical applications such as group MER in crowded environments. Despite considerable advancements in super-resolution techniques for enhancing the quality of LR images and videos, few study has focused on investigate super-resolution for improving LR MER. The scarcity of investigation can be attributed to the inherent difficulty in capturing the subtle motions of micro-expressions, even in original-resolution MER samples, which becomes even more challenging in LR samples due to the loss of distinctive features. Furthermore, a lack of systematic benchmarking and thorough analysis of super-resolution-assisted MER methods has been noted. This paper tackles these issues by conducting a series of benchmark experiments that integrate both super-resolution (SR) and MER methods, guided by an in-depth literature survey. Specifically, we employ seven cutting-edge state-of-the-art (SOTA) MER techniques and evaluate their performance on samples generated from 13 SOTA SR techniques, thereby addressing the problem of super-resolution in MER. Through our empirical study, we uncover the primary challenges associated with SR-assisted MER and identify avenues to tackle these challenges by leveraging recent advancements in both SR and MER methodologies. Our analysis provides insights for progressing toward more efficient SR-assisted MER. Copyright © 2023, The Authors. All rights reserved.

关键词： Image enhancement

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learning a target sample re-generator for cross-database micro-expression recognition

arXiv

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arXiv 2017年

作者： Zong, Yuan Huang, Xiaohua Zheng, Wenming Cui, Zhen Zhao, Guoying Key Laboratory of Child Development and Learning Science of Ministry of Education Research Center for Learning Science Southeast University Nanjing210096 China Center for Machine Vision and Signal Analysis Faculty of Information Technology and Electrical Engineering University of Oulu Oulu FI-90014 Finland School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China

In this paper, we investigate the cross-database micro-expression recognition problem, where the training and testing samples are from two different micro-expression databases. Under this setting, the training and testing samples would have different feature distributions and hence the performance of most existing micro-expression recognition methods may decrease greatly. To solve this problem, we propose a simple yet effective method called Target Sample Re-Generator (TSRG) in this paper. By using TSRG, we are able to re-generate the samples from target micro-expression database and the re-generated target samples would share same or similar feature distributions with the original source samples. For this reason, we can then use the classifier learned based on the labeled source samples to accurately predict the micro-expression categories of the unlabeled target samples. To evaluate the performance of the proposed TSRG method, extensive cross-database micro-expression recognition experiments designed based on SMIC and CASME II databases are conducted. Compared with recent state-of-the-art cross-database emotion recognition methods, the proposed TSRG achieves more promising results. Copyright © 2017, The Authors. All rights reserved.

关键词： Database systems

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Excel in mathematics: Applications of calculus

Excel in mathematics: Applications of calculus

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2010 ASEE Annual Conference and Exposition

作者： Young, Cynthia Georgiopoulos, Michael Crouse, Tace Geiger, Cherie Islas, Alvaro Hagen, Scott Dagley-Falls, Melissa Ramsey, Patricia Lancey, Patrice Department of Mathematics College of Sciences UCF United States School of Electrical Engineering and Computer Science UCF United States Machine Learning Laboratory UCF United States Faculty Center for Teaching and Learning University of Central Florida United States Department of Chemistry College of Sciences UCF United States Civil Environmental and Construction Department UCF United States Coastal Hydroscience Analysis Modeling and Predictive Simulations Laboratory UCF United States Academic Affairs College of Engineering and Computer Science UCF United States Institutional Research University of Central Florida United States Department of Operational Excellence and Assessment Support University of Central Florida United States

Nationally only 40% of the incoming freshmen STEM majors are successful in earning a STEM degree [1]. The University of Central Florida (UCF) EXCEL program is an NSF funded STEP (science, Technology, engineering and Mathematics Talent Expansion Program) whose goal is to increase the number of UCF STEM graduates. One of the activities that EXCEL has identified as essential in retaining students in science and engineering disciplines is the development and teaching of special courses at the freshman level, called Applications of Calculus I and Applications of Calculus II, or Apps I and Apps II, respectively. In Apps I and II, science and engineering professors are asked to lecture twice, as guest lectures, and to demonstrate to students where calculus topics appear in upper level science and engineering classes as well as where faculty use calculus in their research programs. This paper outlines the process used in producing the educational materials for Apps I and II courses (textbook, presentations slides, in-class homework assignments, demos) and it also discusses the assessment results pertaining to this specific EXCEL activity. © American Society for engineering Education, 2010.

关键词： Calculations

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A non-linear approach to solving linear algorithmic problems

A non-linear approach to solving linear algorithmic problems

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Frontiers in Education (FIE) Conference

作者： Orna Muller Bruria Haberman Software Engineering Department Teaching & Learning Center Ort Braude College of Engineering Karmiel Israel Computer Science Department Holon Institute of Technology Israel CS Academia & Industry program for talented high-school Davidson Institute of Science Education Weizmann Institute of Science Rehovot Israel

Solving algorithmic problems and implementing them in code is a major theme in introductory computer science courses. Problems related to string manipulation are common and of great importance in various domains. In the context of computer science education, solving algorithmic problems of this type may be very challenging for novices, even for the more competent students. Analysis of novice students' solutions to a specific class of problems dealing with string manipulation revealed that a widespread intuitive and non-linear approach was used to solve these problems, which led to cumbersome and erroneous solutions. On the other hand, a straightforward linear approach that leads to shorter and more elegant solutions is uncommon. Uncovering students' common and unsatisfactory approaches in problem solving have significant implications on instruction.

关键词： Problem-solving Taxonomy Programming profession Algorithm design and analysis Syntactics

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Work in progress - computing and undergraduate engineering: A collaborative process to align computing education with engineering workforce needs (CPACE)

Work in progress - computing and undergraduate engineering: ...

引用

Frontiers in Education (FIE) Conference

作者： Claudia E. Vergara Mark Urban-Lurain Daina Briedis Neeraj Buch Jeannine LaPrad Louise Paquette Jon Sticklen Thomas F. Wolff Center for Research on College Science Teaching and Learning. MSU USA Instructional Technology Research & Development Division of Science and Mathematics Education College of Natural Science. MSU USA Chemical Engineering and Materials Science. MSU USA Civil and Environmental Engineering. MSU USA CSW USA Math and Computer Science Department. LCC USA Computer Science and Engineering. MSU USA College of Engineering MSU USA

This NSF-funded community-building (CB) project brings together Michigan State University (MSU), Lansing Community College (LCC), and the Corporation for a Skilled Workforce (CSW) to design and implement a process to create a collaboratively defined undergraduate computing education within the engineering and technology fields in alignment with the computational problem-solving abilities needed to transform mid-Michiganpsilas economy and workforce. In this WIP we outline the process we are developing to ensure that a wide variety of stakeholders - business, community leaders and post secondary educators - collaborate to identify workforce computational skills, define how these skills can be integrated across a curriculum, and develop revised curricula that integrate computational problem-solving across engineering departmental courses. By documenting, evaluating and making the process explicit, this process can serve as a model for national efforts to revitalize undergraduate computing education in engineering, and should be extensible to other computing education reform efforts.

关键词： Collaborative work Problem-solving computer science education Business Design engineering Educational institutions Educational programs Educational technology computer science Mirrors

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Interpreting and Navigating Multiple Representations for Computational Thinking in a Robotics Programming Environment

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Journal for STEM Education Research 2018年第1-2期1卷 119-147页

作者： Barth-Cohen, Lauren A. Jiang, Shiyan Shen, Ji Chen, Guanhua Eltoukhy, Moataz Department of Educational Psychology College of Education University of Utah 1721 Campus Center Drive SAEC 3264 Salt Lake City 84112 UT United States Department of Computer Science Carnegie Mellon University Pittsburgh PA United States Department of Teaching and Learning University of Miami 324B Merrick Building 5202 University Drive Coral Gables 33124-2040 FL United States Department of Teaching and Learning University of Miami 312 Merrick Building 5202 University Drive Coral Gables 33124-2040 FL United States Department of Kinesiology and Sport Sciences School of Education & Human Development 1507 Levante Avenue Max Orovitz Building Room 132 Coral Gables 33146 FL United States

Although researchers have proposed different definitions for Computational Thinking (CT), one commonality across these definitions is the emphasis on having students formulate and solve problems in various learning environments, including programming. The continuing attention to CT highlights the need for studies that examine students’, especially elementary students, problem-solving processes. The current study investigates how fifth graders engaged in CT problem-solving activities in a programming environment. Focusing on multiple representations embedded in the CT problem-solving processes, we analyze data of fifth graders who were engaged in a pair-programming robotics interview. In the interview, students navigate multiple representations, such as task instructions, a coding window, and outputs, and in the case of robotics programming activities, a physical robot. The results show that as students were participating in a variety of coding and problem-solving practices, they were interpreting and navigating information within the code window, across the code window and task instructions, across the code window and physical robot, and across all three representations. Informed by these findings, we propose a framework to conceptualize how elementary students interpret and navigate multiple representations in CT problem-solving processes, which could guide future studies in analyzing problem-solving processes in similar contexts. Implications on the importance of multiple representations in programming may apply to other CT learning environments as well. © 2018, Springer Nature Switzerland AG.

关键词： Computational thinking Representations Robotics education

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Developing AI-Based Automated Post-Rating System to Scaffold Interdisciplinary Knowledge-Sharing

Developing AI-Based Automated Post-Rating System to Scaffold...

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International Conference on Advanced learning Technologies (ICALT)

作者： Chia-Kai Chang Po-Chung Chen Zih-Syun Chen Tonny Menglun Kuo Center for General Education National Central University Taoyuan City Taiwan Department of Computer Science and Information Engineering National Central University Taoyuan City Taiwan Department of Civil Engineering National Central University Taoyuan City Taiwan Center for Teaching and Learning Development National Tsing Hua University Hsinchu City Taiwan

Interdisciplinary knowledge sharing is a crucial component of higher education. The use of asynchronous online discussion forums as a medium for fostering interdisciplinary knowledge sharing is effective, as it allows for the sharing, posting, and reflecting of information among learners outside of traditional classroom settings. However, the sheer volume of posts in such forums can threaten the quality of discussion and the ability of instructors to provide timely evaluations. To address this issue, an automated post-rating system has been developed utilizing a BERT-based AI model. This system evaluates learners' posts and provides prompt categorization outcomes into three categories: non-informative, informative, and neutral, within 10 seconds. Our model demonstrated appropriate accuracy in assessing the information density in forum posts, indicating potential benefits for both learners and instructors. Specifically, it achieved 67%, 68%, and 75% accuracy rates for posts categorized as discussion, comment, and reply, respectively. To assess the effectiveness of the system, it was tested and evaluated using two courses, “Python Programming” and “Introduction to AI,” through the use of a questionnaire. Results revealed that learners held positive evaluations of the system, noting improvements in post quality, reduced plagiarism, and enhanced comprehension. Additionally, feedback from open-ended questions also indicated the benefits of automatic feedback on post quality.

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Cross-database micro-expression recognition: A benchmark

arXiv

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arXiv 2018年

作者： Zong, Yuan Zhang, Tong Zheng, Wenming Hong, Xiaopeng Tang, Chuangao Cui, Zhen Zhao, Guoying Key Laboratory of Child Development and Learning Science of Ministry of Education School of Biological Sciences and Medical Engineering Southeast University Nanjing210096 China School of Computer Science and Engineering South China University of Technology Guangzhou510006 China Xi’an Jiao Tong University Xi’an710049 China Center for Machine Vision and Signal Analysis University of Oulu Finland School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China

Cross-database micro-expression recognition (CDMER) is one of recently emerging and interesting problem in micro-expression analysis. CDMER is more challenging than the conventional micro-expression recognition (MER), because the training and testing samples in CDMER come from different micro-expression databases, resulting in the inconsistency of the feature distributions between the training and testing sets. In this paper, we contribute to this topic from three aspects. First, we establish a CDMER experimental evaluation protocol aiming to allow the researchers to conveniently work on this topic and provide a standard platform for evaluating their proposed methods. Second, we conduct benchmark experiments by using NINE state-of-the-art domain adaptation (DA) methods and SIX popular spatiotemporal descriptors for respectively investigating CDMER problem from two different perspectives. Third, we propose a novel DA method called region selective transfer regression (RSTR) to deal with the CDMER task. Our RSTR takes advantage of one important cue for recognizing micro-expressions, i.e., the different contributions of the facial local regions in MER. The overall superior performance of RSTR demonstrates that taking into consideration the important cues benefiting MER, e.g., the facial local region information, contributes to develop effective DA methods for dealing with CDMER problem. Copyright © 2018, The Authors. All rights reserved.

关键词： Database systems

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Validity and Fairness of an Automated Assessment of Creativity in Computational Music Remixing

Validity and Fairness of an Automated Assessment of Creativi...

引用

2023 Workshop on Automated Assessment and Guidance of Project Work, AAGPW 2023

作者： Rahimi, Seyedahmad Smith, Jason Brent Truesdell, Erin J.K. Vinay, Ashvala Boyer, Kristy Elizabeth Magerko, Brian Freeman, Jason McKlin, Tom School of Teaching & Learning College of Education University of Florida GainesvilleFL32611 United States Georgia Tech Center for Music Technology 840 McMillan Street NW AtlantaGA30308 United States Expressive Machinery Lab. Georgia Institute of Technology AtlantaGA30308 United States Computer & Information Science & Engineering University of Florida GainesvilleFL32611 United States The Findings Group DecaturGA30030 United States

Creativity is one of the most crucial skills for success in life in the 21st century. However, assessing creativity in an automated, objective way is challenging. In this study, we designed and validated an automated assessment (an unobtrusive, formative assessment) of creativity in EarSketch, a computational music remixing platform where students write Python or JavaScript code to create pieces of music. Specifically, using an existing dataset of EarSketch projects (n = 53), we investigated the validity and fairness of an automated assessment of creativity. Our findings show that the automated assessment of creativity has reasonable convergent validity (r = .50) and discriminant validity;and this assessment is fair (i.e., no significant differences in terms of gender, grade, or race were found). The results of this research have the potential to inform the design of innovative educational programs and interventions that foster creativity and innovation in STEM education. As we continue to explore new ways of assessing creativity, we can pave the way for a more creative and innovative society, where individuals are equipped with the skills they need to tackle future challenges. © 2023 Copyright for this paper by its authors.

关键词： Automation

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