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关键词： Multimodal generative AI   ChatGPT-4 vision   educational assessment   computer science education  

摘要： The recent integration of visual capabilities into Large Language Models (LLMs) has the potential to play a pivotal role in science and technology education, where visual elements such as diagrams, charts, and tables are commonly used to improve the learning experience. This study investigates the performance of ChatGPT-4 Vision, OpenAI's most advanced visual model at the time the study was conducted, on the Bachelor in Computer Science section of Brazil's 2021 National Undergraduate Exam (ENADE). By presenting the model with the exam's open and multiple-choice questions in their original image format and allowing for reassessment in response to differing answer keys, we were able to evaluate the model's reasoning and self- reflecting capabilities in a large-scale academic assessment involving textual and visual content. ChatGPT-4 Vision significantly outperformed the average exam participant, positioning itself within the top 10 best score percentile. While it excelled in questions that incorporated visual elements, it also encountered challenges with question interpretation, logical reasoning, and visual acuity. A positive correlation between the model's performance in multiple-choice questions and the performance distribution of the human participants suggests multimodal LLMs can provide a useful tool for question testing and refinement. However, the involvement of an independent expert panel to review cases of disagreement between the model and the answer key revealed some poorly constructed questions containing vague or ambiguous statements, calling attention to the critical need for improved question design in future exams. Our findings suggest that while ChatGPT-4 Vision shows promise in multimodal academic evaluations, human oversight remains crucial for verifying the model's accuracy and ensuring the fairness of high-stakes educational exams. The paper's research materials are publicly available at https://***/nabormendonca/gpt-4v-enade-cs-2021.

关键词： Student-generated content   Sustainability   Project-based learning   Peer learning  

摘要： Teaching and learning methods that are related to student-generated content (SGC) seem a promising strategy for including sustainable development goals (SDGs) in education (established as a fundamental cornerstone in the achievement of these goals by the United Nations). This paper describes the inclusion of SDGs through the implementation of website learning projects, whose products are SGC where materials developed by students can be made available to other students (from the same or different courses) in Project Management subjects of the Degree in Computer Science. The method has trialled at two different universities working in a coordinated way. A total of 301 students developed these projects with which they completed the content of the subject, in addition to achieving learning with respect to the SDGs, increasing their understanding of the impact of information and communication technologies on the SDGs, and their awareness of the related problems. We also found that more learning is perceived with information search and content generation activities than with those that focus on the use of materials produced by peers. Finally, it is observed that the method has similar results in different contexts and with different groups of students.

关键词： Computational Thinking   Computer Science   Early Childhood Education   Developmentally Appropriate Practice   Curriculum Design Consideration  

摘要： Many K-12 computer science (CS) education initiatives at the local, state, and federal levels have recently started to focus on engaging the young children. Although most CS education research has focused on the secondary level, only minimal research has explored how computer science (CS) and computational thinking (CT) can be taught in elementary and especially at kindergarten. Understanding how CS and CT are taught at the youngest levels is critical to support the creation of progressive quality curricula and professional development. Therefore, in this study, we delved into the CT/CS curriculum design considerations of five teachers for kindergarteners. Our findings revealed that the primary learning objectives encompassed: 1) Social skill acquisition, 2) Fostering a growth mindset, and 3) Developing basic CT competencies. Moreover, when crafting their CT/CS curriculum, teachers weighed factors such as 1) Their approach to adapting the CT/CS curriculum-whether it be a personalized approach or relying on a pre-packaged curriculum-and 2) Adhering to Developmentally Appropriate Practice (DAP), which took into account individual abilities, interests, and socially relevant contexts. We conclude by discussing the ramifications of these findings in terms of professional development and the shaping of future CT/CS curricula for young learners.

关键词： Noise measurement   Sparse matrices   Linear matrix inequalities   Computer science   Complexity theory   Upper bound   Pollution measurement   Leverage score   low rank   matrix completion   noise  

摘要： Completing low-rank matrices from subsampled measurements has received much attention in the past decade. Existing works indicate that O(nr log(2)(n)) datums are required to theoretically secure the completion of an n x n noisy matrix of rank r with high probability, under some quite restrictive assumptions: 1) the underlying matrix must be incoherent and 2) observations follow the uniform distribution. The restrictive-ness is partially due to ignoring the roles of the leverage score and the oracle information of each element. In this article, we employ the leverage scores to characterize the importance of each element and significantly relax assumptions to: 1) not any other structure assumptions are imposed on the underlying low-rank matrix and 2) elements being observed are appropriately dependent on their importance via the leverage score. Under these assumptions, instead of uniform sampling, we devise an ununiform/biased sampling procedure that can reveal the "importance" of each observed element. Our proofs are supported by a novel approach that phrases sufficient optimality conditions based on the Golfing scheme, which would be of independent interest to the wider areas. Theoretical findings show that we can provably recover an unknown n x n matrix of rank r from just about O(nr log(2)(n)) entries, even when the observed entries are cor-rupted with a small amount of noisy information. The empirical results align precisely with our theories.

关键词： Coding teaching self-efficacy scale (CTSES)   Computer science education   Self-efficacy assessment   Coding instruction   Scale development   Teacher self-efficacy  

摘要： The significance of teachers' self-efficacy in coding education within K-12 settings has grown substantially. However, the literature lacks subject-specific measurement tools tailored to assess teachers' self-efficacy in coding instruction. This study adopted a mixed methods approach to develop a reliable and valid instrument for measuring computer science (CS) teachers' self-efficacy in teaching coding. The scale development involved a rigorous process encompassing item generation, expert validation, and pilot testing. Importantly, this process unfolded in seven steps with two distinct phases, and each phase involved independent sample groups. Subsequently, a comprehensive survey was administered to two samples of CS teachers (n = 318, n = 295) to assess the scale's psychometric properties. The results revealed robust internal consistency and construct validity of the 20-item Coding Teaching Self-Efficacy Scale (CTSES) with four intercorrelated dimensions: student motivation, subject knowledge, classroom management, and material development. Furthermore, additional analyses revealed the significant impact of teaching experience and self-reported coding knowledge level on teachers' self-efficacy in teaching coding. The implications of this study hold significance for both practitioners and researchers to understand teachers' self-efficacy in teaching coding and to explore its relation to teacher training, curriculum development, and the broader advancement of coding education within school settings.

关键词： business process innovation   human capital   machine learning   noncompete agreements   worker mobility  

摘要： Research SummaryWe investigate how worker mobility influences the adoption of a new technology using state-level changes to the enforceability of noncompete agreements as an exogenous shock to worker mobility. Using data on over 153,000 establishments from 2010 and 2018, we find that changes that facilitate worker movements are associated with a significant decline in the likelihood of adoption of machine learning. Moreover, we find that the magnitude of decline depends upon the size of the establishment, the extent of predictive analytics adoption in its industry, and the number of large establishments in the same industry-location. These results are consistent with the view that increases in outward worker mobility increase costs for adoption of a new technology that involves significant downstream investments in the early years of its *** SummarySuccessful business adoption of new technologies such as machine learning requires skilled workers with experience in implementing those technologies. In the early years of technology diffusion workers in early adopting businesses typically acquire these skills through on-the-job learning that is paid for by the adopter. So, if such early adopters face an increased risk of those skilled workers quitting, then their incentives to adopt the technology decrease. We examine this possibility using changes in noncompete enforceability as a proxy for changes in worker mobility and find that the likelihood of adopting machine learning decreases as the risk of worker mobility increases, particularly for larger establishments, establishments in industries where adoption may be more beneficial and in locations with many large competing establishments.

关键词： gaze estimation   human-machine interface   interactive art   the elderly   active aging  

摘要： The impact of global population aging on older adults' health and emotional well-being is examined in this study, emphasizing innovative technological solutions to address their diverse needs. Changes in physical and mental functions due to aging, along with emotional challenges that necessitate attention, are highlighted. Gaze estimation and interactive art are utilized to develop an interactive system tailored for elderly users, where interaction is simplified through eye movements to reduce technological barriers and provide a soothing art experience. By employing multi-sensory stimulation, the system aims to evoke positive emotions and facilitate meaningful activities, promoting active aging. Named "Natural Rhythm through Eyes", it allows for users to interact with nature-themed environments via eye movements. User feedback via questionnaires and expert interviews was collected during public demonstrations in elderly settings to validate the system's effectiveness in providing usability, pleasure, and interactive experience for the elderly. Key findings include the following: (1) Enhanced usability of the gaze estimation interface for elderly users. (2) Increased enjoyment and engagement through nature-themed interactive art. (3) Positive influence on active aging through the integration of gaze estimation and interactive art. These findings underscore technology's potential to enhance well-being and quality of life for older adults navigating aging challenges.

关键词： Karnaugh maps   Quine-McCluskey method   ICT tool-based learning   Virtual labs  

摘要： A Study with undergraduate engineering students was conducted in order to evaluate whether cognitive and comprehending ability can be improved by incorporating the tool based learning. The simulator tools and virtual labs were used to represent tool based learning. The study was conducted on three different years of students. In the first stage course content was delivered using the traditional mode that is chalk and board and later the same content was delivered using software tools having visualization effects. A total of 422 students participated in the study. Pre-tool and post-tool learning tests were conducted, a statistical analysis was done to understand the effects of tool-based learning on cognitive and comprehending ability of the students using the concept of minimization of the given boolean expression, which can be solved in two methods which depends on cognitive ability and Quine-McCluskey (QMC) method which depends on the comprehending ability of the student. A survey was conducted to gauge the learning experience of the students. In this experimental research process data is collected on pre and post tool learning along with analysis of students learning outcomes. The findings indicate a significant positive effect of software tool based learning approach on student's ability to minimize the Boolean expression. The research aims at filling the gap of understanding software tools role in teaching and learning process.

关键词： Remaining useful life prediction   Multi-sensor fusion   Nonlinear Wiener process   Sparse Bayesian  

摘要： Accurate remaining useful life (RUL) prediction plays a vital role in increasing the system operation safety and reducing maintenance costs. In industrial applications, there is usually a large amount of multi-sensor data generated. Therefore, how to construct an appropriate health index (HI) based on multi-sensor signals is very important for the RUL prediction. However, existing works treat sensor selection, HI construction, and degradation modeling independently as unrelated parts, which may result in the combination of sensors selected not constituting an optimal HI or the constructed HI not matching the degradation model. In addition, most existing works treat prior units as a whole to obtain a unique set of sensor combinations and fusion coefficients, which cannot reflect unit-to-unit heterogeneity, thus affecting the accuracy of RUL prediction. Therefore, a novel interactive feedback framework is established to construct HI, where the sensor selection, fusion coefficient calculation, and nonlinear Wiener process degradation modeling are incorporated into the feedback. Furthermore, an adaptive weight selection method based on particle swarm optimization and leave- one-out cross-validation (PSO-LV) is proposed to adjust the fusion coefficients in real-time. Then, the RUL is estimated by updating model parameters online, detecting degradation trends, and deriving the probability density function (PDF) of the RUL. Finally, two examples of engine datasets are provided to verify the effectiveness of the proposed method.

关键词： Educational technology   Technology Acceptance Model (TAM)   Student perceptions   Technology adoption   Higher education  

摘要： In recent years, online educational platforms have become an increasingly popular tool for delivering online learning experiences. One such platform is the Tunisian educational platform provided by the Virtual University of Tunis. The acceptance and adoption of these platforms by students are crucial for their successful integration into the educational system. This study investigates students' intentions towards the use of the Tunisian educational platform using the proposed Extended Technology Acceptance Model (e-TAM). An empirical study was conducted involving 108 undergraduate computer science students from a Tunisian public university, providing insights into students' intentions and contributing to a deeper understanding into the factors driving the adoption of educational technology. The findings of this study contribute to the literature by validating an extension of TAM in the Tunisian context and providing valuable insights for educators, policymakers, and platform developers to improve the design, usability, and effectiveness of these platforms.