Knowledge convergence in computer-supported collaborative learning

This study investigates how two types of graphical representation tools influence the way in which learners use knowledge resources in two different collaboration conditions. In addition, the study explores the extent to which learners share knowledge with respect to individual outcomes under these different conditions. The study also analyzes the relationship between the use of knowledge resources and different types of knowledge. The type of external representation (content-specific vs. content-independent) and the collaboration condition (videoconferencing vs. face-to-face) were varied. Sixty-four (64) university students participated in the study. Results showed that learning partners converged strongly with respect to their use of resources during the collaboration process. Convergence with respect to outcomes was rather low, but relatively higher for application-oriented knowledge than for factual knowledge. With content-specific external representation, learners used more appropriate knowledge resources without sharing more knowledge after collaboration. Learners in the computer-mediated collaboration used a wider range of resources. Moreover, in exploratory qualitative and quantitative analyses, the study found evidence for a relation between aspects of the collaborative process and knowledge convergence

Cross-task weakly supervised learning from instructional videos

In this paper we investigate learning visual models for the steps of ordinary tasks using weak supervision via instructional narrations and an ordered list of steps instead of strong supervision via temporal annotations. At the heart of our approach is the observation that weakly supervised learning may be easier if a model shares components while learning different steps: `pour egg' should be trained jointly with other tasks involving `pour' and `egg'. We formalize this in a component model for recognizing steps and a weakly supervised learning framework that can learn this model under temporal constraints from narration and the list of steps. Past data does not permit systematic studying of sharing and so we also gather a new dataset, CrossTask, aimed at assessing cross-task sharing. Our experiments demonstrate that sharing across tasks improves performance, especially when done at the component level and that our component model can parse previously unseen tasks by virtue of its compositionality.Comment: 18 pages, 17 figures, to be published in proceedings of the CVPR, 201

Learning to Localize and Align Fine-Grained Actions to Sparse Instructions

Automatic generation of textual video descriptions that are time-aligned with video content is a long-standing goal in computer vision. The task is challenging due to the difficulty of bridging the semantic gap between the visual and natural language domains. This paper addresses the task of automatically generating an alignment between a set of instructions and a first person video demonstrating an activity. The sparse descriptions and ambiguity of written instructions create significant alignment challenges. The key to our approach is the use of egocentric cues to generate a concise set of action proposals, which are then matched to recipe steps using object recognition and computational linguistic techniques. We obtain promising results on both the Extended GTEA Gaze+ dataset and the Bristol Egocentric Object Interactions Dataset

Knowledge convergence in collaborative learning

In collaborative learning the question has been raised as to how learners in small groups influence one another and converge or diverge with respect to knowledge. Knowledge convergence can be conceptualised as knowledge equivalence and as shared knowledge prior to, during, and subsequent to collaborative learning. Knowledge equivalence refers to learners becoming more similar to their learning partners with regard to the extent of their individual knowledge. Shared knowledge means that learners have knowledge on the very same concepts as their learning partners. In this article, we provide measures for assessing both, knowledge equivalence and shared knowledge

Learning For Life: The Opportunity for Technology to Transform Adult Education - Part l: Interest In and Aptitude for Technology

In fall 2014, Tyton Partners (formerly Education Growth Advisors), with support from the Joyce Foundation, conducted national research on the role and potential of instructional technology in the US adult education field. The objective was to understand the current state of the field with respect to technology readiness and the opportunities and challenges for increasing the use of technology-based instructional models within adult education. Through two publications, we will present the findings from our research and propose key questions and ideas to catalyze conversations among adult education leaders and practitioners, policy makers, education suppliers and entrepreneurs, and foundations and funders regarding the gaps in the adult education system and opportunities for leveraging technology to better meet the needs of underprepared adult learners. The briefs will address both demandside and supply-side dynamics.This initial publication focuses on the demand side and addresses adult education administrators' and practitioners' perspectives on the role and potential of technology to support their students' needs and objectives

Exploring the episodic structure of algebra story problem solving

This paper analyzes the quantitative and situational structure of algebra story problems, uses these materials to propose an interpretive framework for written problem-solving protocols, and then presents an exploratory study of the episodic structure of algebra story problem solving in a sizable group of mathematically competent subjects. Analyses of written protocols compare the strategic, tactical, and conceptual content of solution attampts, looking within these attempts at the interplay between problem comprehension and solution. Comprehension and solution of algebra story problems are complimentary activities, giving rise to a succession of problem solving episodes. While direct algebraic problem solving is sometimes effective, results suggest that the algebraic formalism may be of little help in comprehending the quantitative constraints posed in a problem text. Instead, competent problem solvers often reason within the situational context presented by a story problem, using various forms of "model-based reasoning" to identify, pursue, and verify quantitative constraints required for solution. The paper concludes by discussing the implications of these findings for acquiring mathematical concepts (e.g., related linear functions) and for supporting their acquisition through instruction

Towards developing a collaborative video platform for learning

The work presented in this paper outlines issues relating to the development of a collaborative video platform for learning. Student adoption of collaborative and video technology is increasing dramatically, becoming part of their everyday lives. The aim of this paper is to propose a system and framework for the successful integration of these technologies into teaching and learning. At the outset we assess current trends and previous research, using these findings to inform the development of a new platform. System specifications are then presented with specific needs identified for students and educators. Finally our tentative framework for a integrating a collaborative video platform for learning is presented

Market scenarios and alternative administrative frameworks for US educational satellite systems

Costs and benefits of developing an operational educational satellite system in the U.S. are analyzed. Scenarios are developed for each educational submarket and satellite channel and ground terminal requirements for a large-scale educational telecommunications system are estimated. Alternative organizational frameworks for such a system are described