Distributed visual environment for teaching algorithms

Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.Includes bibliographical references (leaves 56-58).by Aaron T.T. BoydS.B.and M.Eng

Leveraging Text-to-Scene Generation for Language Elicitation and Documentation

Text-to-scene generation systems take input in the form of a natural language text and output a 3D scene illustrating the meaning of that text. A major benefit of text-to-scene generation is that it allows users to create custom 3D scenes without requiring them to have a background in 3D graphics or knowledge of specialized software packages. This contributes to making text-to-scene useful in scenarios from creative applications to education. The primary goal of this thesis is to explore how we can use text-to-scene generation in a new way: as a tool to facilitate the elicitation and formal documentation of language. In particular, we use text-to-scene generation (a) to assist field linguists studying endangered languages; (b) to provide a cross-linguistic framework for formally modeling spatial language; and (c) to collect language data using crowdsourcing. As a side effect of these goals, we also explore the problem of multilingual text-to-scene generation, that is, systems for generating 3D scenes from languages other than English. The contributions of this thesis are the following. First, we develop a novel tool suite (the WordsEye Linguistics Tools, or WELT) that uses the WordsEye text-to-scene system to assist field linguists with eliciting and documenting endangered languages. WELT allows linguists to create custom elicitation materials and to document semantics in a formal way. We test WELT with two endangered languages, Nahuatl and Arrernte. Second, we explore the question of how to learn a syntactic parser for WELT. We show that an incremental learning method using a small number of annotated dependency structures can produce reasonably accurate results. We demonstrate that using a parser trained in this way can significantly decrease the time it takes an annotator to label a new sentence with dependency information. Third, we develop a framework that generates 3D scenes from spatial and graphical semantic primitives. We incorporate this system into the WELT tools for creating custom elicitation materials, allowing users to directly manipulate the underlying semantics of a generated scene. Fourth, we introduce a deep semantic representation of spatial relations and use this to create a new resource, SpatialNet, which formally declares the lexical semantics of spatial relations for a language. We demonstrate how SpatialNet can be used to support multilingual text-to-scene generation. Finally, we show how WordsEye and the semantic resources it provides can be used to facilitate elicitation of language using crowdsourcing

Model-based, event-driven programming paradigm for interactive web applications

Applications are increasingly distributed and event-driven. Advances in web frameworks have made it easier to program standalone servers and their clients, but these applications remain hard to write. A model-based programming paradigm is proposed that allows a programmer to represent a distributed application as if it were a simple sequential program, with atomic actions updating a single, shared global state. A runtime environment executes the program on a collection of clients and servers, automatically handling (and hiding from the programmer) complications such as network communication (including server push), serialization, concurrency and races, persistent storage of data, and queuing and coordination of events.National Science Foundation (U.S.) (Grant CCF-1138967)National Science Foundation (U.S.) (Grant CCF-1012759)National Science Foundation (U.S.) (Grant CCF-0746856

Algorithm animation in a declarative visual programming language

How might capabilities for algorithm animation be seamlessly integrated into a programming language that is both visual and declarative? Until now, visual programming language researchers have not attempted to answer that question, making the fruits of algorithm animation available only to users of textual progranming languages. Users of visual programming languages (VPLs) have been deprived of the unique semantic insights algorithm animation offers, insights that would foster the understanding and debugging of visual programs. We have answered the question by seamlessly integrating algorithm animation capabilities into Forms/3, a general-purpose, declarative VPL. Our results show that such a VPL can support algorithm animation without leaving the declarative, visual model, without adding new concepts to the language or how to program in it, and without deviating from the uniform representation established for the language. In addition, our research shows that the characteristics of declarative VPLs result in some interesting algorithm animation features not found in other systems

Proceedings of the Second Program Visualization Workshop, 2002

The Program Visualization Workshops aim to bring together researchers who design and construct program visualizations and, above all, educators who use and evaluate visualizations in their teaching. The first workshop took place in July 2000 at Porvoo, Finland. The second workshop was held in cooperation with ACM SIGCSE and took place at HornstrupCentret, Denmark in June 2002, immediately following the ITiCSE 2002 Conference in Aarhus, Denmark

AN EXPLORATORY CONSTRUCTIVIST GROUNDED THEORY STUDY: HOW SECONDARY SCHOOL SCIENCE TEACHERS INTERPRET STUDENTS’ SCIENTIFIC MODELS THAT ARE COMPRISED OF DRAWING ACTIVITIES

Extant literature lacks an explanation of the thought processes used by secondary school science teachers to interpret students’ scientific models that are comprised of drawing activities. In this exploratory study, a constructivist grounded theory (CGT) was developed to generate an interpretive understanding. The CGT was generated from observations, interviews, and document analyses of five research participants consisting of secondary school science teachers from lower New York State. To generate a CGT, concepts, terms, assumptions, and definitions from selected theories—decolonizing methodologies theory (DMT), visual semiotic theory (VST), and cultural studies theory (CST)—collectively provided a fresh onto-epistemological lens for initially examining and bringing transparency to the invisible influences on the intangible thought processes of science teachers when they interpret students’ scientific models. At the end of the study, a CGT was developed which is expressed as nine assertions, a diagrammatic display/axial coding paradigm, and an explanation consisting of found poetry developed from the research findings. Using reflective and reflexive analytical memos, this study revealed that the thoughts of secondary school science teachers consist of five themes: (1) direction or rules, (2) forms of communication, (3) creations (4) interpretation or understanding, and (5) problem-solving heuristics during students’ struggle. In addition, the theory illustrated that in the context of lower New York State, science disciplinary culture works by crossing borders (Aikenhead & Elliott, 2010; Carter, 2011; New York State Education Department, 2019a; Rasheed, 2001, 2006; Snively & Corsiglia, 2001) between Western cultural thoughts and non-Western/Indigenous cultural thoughts. This study will benefit both stakeholders and scholars. For stakeholders, this study offers a substantive theory for understanding the assessment practices of science teachers. For scholars, this study provides a CGT that integrates theories/subdisciplines that are epistemologically distant/close and generates ongoing research. In particular, the theory provides scholars with findings that can be used to subsequently conduct a quantitative study, whereby a culturally sensitive survey instrument can be generated and validated

Factors Underlying Students' Conceptions of Deep Time: An Exploratory Study

ABSTRACT Geologic or “deep time” is important for understanding many geologic processes. There are two aspects to deep time. First, events in Earth’s history can be placed in temporal order on an immense time scale (succession). Second, rates of geologic processes vary significantly. Thus, some events and processes require time periods (durations) that are outside a human lifetime by many orders of magnitude. Previous research has demonstrated that learners of all ages and many teachers have poor conceptions of succession and duration in deep time. The question is why. This exploratory, qualitative study investigates the viability of a model (a deep time stool) to capture the underlying factors necessary for a concept of deep time. The model posits that a concept of deep time rests upon: an understanding of succession and duration in conventional time; a robust understanding of large numbers and the proportional relationships among numbers of various magnitudes; and a learner’s geoscience content knowledge. While all three factors may not exist to the same degree in any one individual, all must be present to support a conception of deep time. Thirty-five students in the United States participated in individual task-based interviews: 12 eighth and 11 eleventh graders from a public charter school in the U.S. and 12 university students from two institutions enrolled in an introductory geoscience course. Tasks and questions probed students’ understandings of the three factors within and outside a deep time context, and the study is unique for that reason. Results indicate all three factors play an important role in how students understand deep time. While succession in conventional time proved non-problematic, duration was more difficult for participants. Some students were confused about the relationships among numbers in the thousands and millions, and others appeared to have little understanding of time periods up to 100 years. Participants had just as much difficulty dealing with the duration for events in conventional time as they did for those in deep time if the events were unfamiliar to them. Time and number share a similar spatial mapping strategy while knowledge of large numbers and geoscience content knowledge appear to provide reference points that can be used to judge the temporal order or duration of geoscience events. Implications for future research and classroom practice are discussed