475 research outputs found
Sensor-Free or Sensor-Full: A Comparison of Data Modalities in Multi-Channel Affect Detection
ABSTRACT Computational models that automatically detect learners' affective states are powerful tools for investigating the interplay of affect and learning. Over the past decade, affect detectors-which recognize learners' affective states at run-time using behavior logs and sensor data-have advanced substantially across a range of K-12 and postsecondary education settings. Machine learningbased affect detectors can be developed to utilize several types of data, including software logs, video/audio recordings, tutorial dialogues, and physical sensors. However, there has been limited research on how different data modalities combine and complement one another, particularly across different contexts, domains, and populations. In this paper, we describe work using the Generalized Intelligent Framework for Tutoring (GIFT) to build multi-channel affect detection models for a serious game on tactical combat casualty care. We compare the creation and predictive performance of models developed for two different data modalities: 1) software logs of learner interactions with the serious game, and 2) posture data from a Microsoft Kinect sensor. We find that interaction-based detectors outperform posture-based detectors for our population, but show high variability in predictive performance across different affect. Notably, our posture-based detectors largely utilize predictor features drawn from the research literature, but do not replicate prior findings that these features lead to accurate detectors of learner affect
The impact of STEM experiences on student self-efficacy in computational thinking
Citation: Weese, J. L., Feldhausen, R., & Bean, N. H. (2016). The impact of STEM experiences on student self-efficacy in computational thinking.Since the introduction of new curriculum standards at K-12 schools, computational thinking has become a major research area. Creating and delivering content to enhance these skills, as well as evaluation, remain open problems. This paper describes two different interventions based on the Scratch programming language which aim to improve student self-efficacy in computer science and computational thinking. The two interventions were applied at a STEM outreach program for 5th-9th grade students. Previous experience in STEM related activities and subjects, as well as student self-efficacy, were collected using a developed pre- and post-survey. We discuss the impact of our intervention on student performance and confidence, and evaluate the validity of our instrument. © American Society for Engineering Education, 2016
Agents for educational games and simulations
This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications
Open Access Publishing: A Literature Review
Within the context of the Centre for Copyright and New Business Models in the Creative Economy (CREATe) research scope, this literature review investigates the current trends, advantages, disadvantages, problems and solutions, opportunities and barriers in Open Access Publishing (OAP), and in particular Open Access (OA) academic publishing. This study is intended to scope and evaluate current theory and practice concerning models for OAP and engage with intellectual, legal and economic perspectives on OAP. It is also aimed at mapping the field of academic publishing in the UK and abroad, drawing specifically upon the experiences of CREATe industry partners as well as other initiatives such as SSRN, open source software, and Creative Commons. As a final critical goal, this scoping study will identify any meaningful gaps in the relevant literature with a view to developing further research questions. The results of this scoping exercise will then be presented to relevant industry and academic partners at a workshop intended to assist in further developing the critical research questions pertinent to OAP
Awareness support for learning designers in collaborative authoring for adaptive learning
Adaptive learning systems offer students a range of appropriate learning options based on the learnersâ characteristics. It is, therefore, necessary for such systems to maintain a hyperspace and knowledge space that consists of a large volume of domain and pedagogical knowledge, learner information, and adaptation rules. As a consequence, for a solitary teacher, developing learning resources would be time consuming and requires the teacher to be an expert of many topics. In this research, the problems of authoring adaptive learning resources are classified into issues concerning interoperability, efficiency, and collaboration.This research particularly addresses the question of how teachers can collaborate in authoring adaptive learning resources and be aware of what has happened in the authoring process. In order to experiment with collaboration, it was necessary to design a collaborative authoring environment for adaptive learning. This was achieved by extending an open sourced authoring tool of IMS Learning Design (IMS LD), ReCourse, to be a prototype of Collaborative ReCourse that includes the workspace awareness information features: Notes and History. It is designed as a tool for asynchronous collaboration for small groups of learning designers. IMS LD supports interoperability and adaptation. Two experiments were conducted. The first experiment was a workspace awareness study in which participants took part in an artificial collaborative scenario. They were divided into 2 groups; one group worked with ReCourse, the other with Collaborative ReCourse. The results provide evidence regarding the advantages of Notes and History for enhancing workspace awareness in collaborative authoring of learning designs.The second study tested the system more thoroughly as the participants had to work toward real goals over a much longer time frame. They were divided into four groups; two groups worked with ReCourse, while the others worked with Collaborative ReCourse. The experiment result showed that authoring of learning designs can be approached with a Process Structure method with implicit coordination and without role assignment. It also provides evidence that collaboration is possible for authoring IMS LD Level A for non-adapting and Level B for adapting materials. Notes and History assist in producing good quality output.This research has several contributions. From the literature study, it presents a comparison analysis of existing authoring tools, as well as learning standards. Furthermore, it presents a collaborative authoring approach for creating learning designs and describes the granularity level on which collaborative authoring for learning designs can be carried out. Finally, experiments using this approach show the advantages of having Notes and History for enhancing workspace awareness that and how they benefit the quality of learning designs
Interim research assessment 2003-2005 - Computer Science
This report primarily serves as a source of information for the 2007 Interim Research Assessment Committee for Computer Science at the three technical universities in the Netherlands. The report also provides information for others interested in our research activities
Improving National and Homeland Security through a proposed Laboratory for Information Globalization and Harmonization Technologies (LIGHT)
A recent National Research Council study found that: "Although there are many private and public databases that
contain information potentially relevant to counter terrorism programs, they lack the necessary context definitions
(i.e., metadata) and access tools to enable interoperation with other databases and the extraction of meaningful and
timely information" [NRC02, p.304, emphasis added] That sentence succinctly describes the objectives of this
project. Improved access and use of information are essential to better identify and anticipate threats, protect
against and respond to threats, and enhance national and homeland security (NHS), as well as other national
priority areas, such as Economic Prosperity and a Vibrant Civil Society (ECS) and Advances in Science and
Engineering (ASE). This project focuses on the creation and contributions of a Laboratory for Information
Globalization and Harmonization Technologies (LIGHT) with two interrelated goals:
(1) Theory and Technologies: To research, design, develop, test, and implement theory and technologies for
improving the reliability, quality, and responsiveness of automated mechanisms for reasoning and resolving semantic
differences that hinder the rapid and effective integration (int) of systems and data (dmc) across multiple
autonomous sources, and the use of that information by public and private agencies involved in national and
homeland security and the other national priority areas involving complex and interdependent social systems (soc).
This work builds on our research on the COntext INterchange (COIN) project, which focused on the integration
of diverse distributed heterogeneous information sources using ontologies, databases, context mediation algorithms,
and wrapper technologies to overcome information representational conflicts. The COIN approach makes it
substantially easier and more transparent for individual receivers (e.g., applications, users) to access and exploit
distributed sources. Receivers specify their desired context to reduce ambiguities in the interpretation of information
coming from heterogeneous sources. This approach significantly reduces the overhead involved in the integration of
multiple sources, improves data quality, increases the speed of integration, and simplifies maintenance in an
environment of changing source and receiver context - which will lead to an effective and novel distributed
information grid infrastructure. This research also builds on our Global System for Sustainable Development
(GSSD), an Internet platform for information generation, provision, and integration of multiple domains, regions,
languages, and epistemologies relevant to international relations and national security.
(2) National Priority Studies: To experiment with and test the developed theory and technologies on practical
problems of data integration in national priority areas. Particular focus will be on national and homeland security,
including data sources about conflict and war, modes of instability and threat, international and regional
demographic, economic, and military statistics, money flows, and contextualizing terrorism defense and response.
Although LIGHT will leverage the results of our successful prior research projects, this will be the first research
effort to simultaneously and effectively address ontological and temporal information conflicts as well as
dramatically enhance information quality. Addressing problems of national priorities in such rapidly changing
complex environments requires extraction of observations from disparate sources, using different interpretations, at
different points in times, for different purposes, with different biases, and for a wide range of different uses and
users. This research will focus on integrating information both over individual domains and across multiple domains.
Another innovation is the concept and implementation of Collaborative Domain Spaces (CDS), within which
applications in a common domain can share, analyze, modify, and develop information. Applications also can span
multiple domains via Linked CDSs. The PIs have considerable experience with these research areas and the
organization and management of such large scale international and diverse research projects.
The PIs come from three different Schools at MIT: Management, Engineering, and Humanities, Arts & Social
Sciences. The faculty and graduate students come from about a dozen nationalities and diverse ethnic, racial, and
religious backgrounds. The currently identified external collaborators come from over 20 different organizations
and many different countries, industrial as well as developing. Specific efforts are proposed to engage even more
women, underrepresented minorities, and persons with disabilities.
The anticipated results apply to any complex domain that relies on heterogeneous distributed data to address and
resolve compelling problems. This initiative is supported by international collaborators from (a) scientific and
research institutions, (b) business and industry, and (c) national and international agencies. Research products
include: a System for Harmonized Information Processing (SHIP), a software platform, and diverse applications in
research and education which are anticipated to significantly impact the way complex organizations, and society in
general, understand and manage critical challenges in NHS, ECS, and ASE
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