1,721,005 research outputs found
A Revised Textual Tree Trace Notation for Prolog
Get PDFThis paper describes a ''textual tree trace'' (TTT) notation for representing the execution of Prolog programs. Compact, textual and non-linear, it provides detailed information about variable binding and execution history, and distinguishes several modes of goal failure. The revised form given here, yet to be empirically tested, is partly informed by Paul Mulholland's empirical comparisons of Prolog trace notations, in which an earlier version of the TTT notation was amongst those studied and criticised. The work presented here is an updated version of a previous workshop paper (Taylor, du Boulay, & Patel, 1994)
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A cognitive dimensions analysis of interaction design for algorithmic composition software
Get PDFThis paper presents an analysis of the user interfaces of a range of algorithmic music composition software using the Cognitive Dimensions of Notations as the main analysis tool. Findings include the following: much of the reviewed software exhibits a low viscosity and requires significant user knowledge. The use of metaphor (staff notation, music production hardware) introduces multiple levels of abstraction which the user has to understand in order to use effectively: some instances of close mapping reduce abstraction but require the user to do more work. Significant premature commitment is not conducive to music composition, and there are clear opportunities for the greater provisionality that a piece of structurally-aware music software could provide. Visibility and juxtaposability are frequently compromised by complex design. Patching software reduces the hard mental operations required of the user by making the signal flow clear, although graphical complexity can have a negative impact on role-expressiveness. Complexity leads to error-proneness in several instances, although there are some tools (such as error-checking and auto-completion) which seek to ameliorate the main problem
Using Natural Language Processing to Analyze Tutorial Dialogue Corpora Across Domains Modalities
Get PDFOur research goal is to investigate whether previous findings and methods in the area of tutorial dialogue can be generalized across dialogue corpora that differ in domain (mechanics versus electricity in physics), modality (spoken versus typed), and tutor type (computer versus human). We first present methods for unifying our prior coding and analysis methods. We then show that many of our prior findings regarding student dialogue behaviors and learning not only generalize across corpora, but that our methodology yields additional new findings. Finally, we show that natural language processing can be used to automate some of these analyses
Manim-DFA:Visualising Data Flow Analysis and Abstract Interpretation Algorithms with Automated Video Generation
Get PDFIn this paper, we introduce Manim-DFA, an extension of the Manim library for generating video visualisations to teach data flow analysis and abstract interpretation. Despite the importance of data flow analysis in static program analysis, educational visualisation tools remain scarce. Manim-DFA addresses this gap by enabling educators to animate control flow graphs and lattice structures, illustrating their transformation during program analysis. Currently, the tool supports automated animation of the worklist algorithm, as well as lattice visu-alisation. Designed with established pedagogical principles, Manim-DFA promotes active learning, reduces cognitive load, and enhances conceptual understanding. Preliminary evaluations suggest that it effectively complements traditional resources and supports autonomous learning
Toward Automated UML Diagram Assessment:Comparing LLM-Generated Scores with Teaching Assistants
Get PDFThis paper investigates the feasibility of using Large Language Models (LLMs) to automate the grading of Unified Modeling Language (UML) class diagrams in a software design course. Our method involves carefully designing case studies with constraints that guide students’ design choices, converting visual diagrams to textual descriptions, and leveraging LLMs’ natural language processing capabilities to evaluate submissions. We evaluated our approach using 92 student submissions, comparing grades assigned by three teaching assistants with those generated by three LLMs (Llama, GPT o1-mini, and Claude). Our results show that GPT o1-mini and Claude Sonnet achieved strong alignment with human graders, reaching correlation coefficients above 0.76 and Mean Absolute Errors below 4 points on a 40-point scale. The findings suggest that LLM-based grading can provide consistent, scalable assessment of UML diagrams while matching the grading quality of human assessors. This approach offers a promising solution for managing growing student numbers while ensuring fair and timely feedback.</p
Teacher in the Loop:Customizing Educational Games Using Natural Language
Get PDFDespite significant advances in educational technology and design methodologies, current educational games demonstrate a fundamental limitation: educators are unable to modify content after the games are deployed, limiting curriculum alignment and pedagogical customization. This paper introduces Imikathen-VR, a solution built upon a text-to-animation system, supporting K-1 and K-2 teachers to create minigames for their students to practice basic writing skills. Our implementation extends an existing animation pipeline by integrating a fine-tuned T5 model for sentence simplification, achieving 95% F1 BERT score and 76% ROUGE-L score in maintaining semantic and lexical fidelity. We improve visual reasoning by transforming the task of identifying missing visual details into a Masked Language Modeling problem. Preliminary results demonstrate the system's effectiveness in generating curriculum-aligned VR exercises, though comprehensive classroom testing remains pending. This work advances the integration of customizable VR technology in early education, providing teachers with enhanced control over educational content.</p
The "DeMAND" coding scheme: A "common language" for representing and analyzing student discourse
Get PDFWe propose that a set of five dimensions forms a foundation underlying a number of prevalent theoretical perspectives on learning. We show how student contributions to instructional dialogue can be reliably annotated with these dimensions. Finally, we provide preliminary validation evidence for our coding scheme and illustrate the potential value of such an approach to analyzing student behavior in tutorial dialogue
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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