Evaluating the Effectiveness of tutorial dialogue instruction in a Explotary learning context

[Proceedings of] ITS 2006, 8th International Conference on Intelligent Tutoring Systems, 26-30 June 2006, Jhongli, Taoyuan County, TaiwanIn this paper we evaluate the instructional effectiveness of tutorial dialogue agents in an exploratory learning setting. We hypothesize that the creative nature of an exploratory learning environment creates an opportunity for the benefits of tutorial dialogue to be more clearly evidenced than in previously published studies. In a previous study we showed an advantage for tutorial dialogue support in an exploratory learning environment where that support was administered by human tutors [9]. Here, using a similar experimental setup and materials, we evaluate the effectiveness of tutorial dialogue agents modeled after the human tutors from that study. The results from this study provide evidence of a significant learning benefit of the dialogue agentsThis project is supported by ONR Cognitive and Neural Sciences Division, Grant number N000140410107proceedingPublicad

Learning in evolutionary environments

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Learning in Evolutionary Environments

The purpose of this work is to present a sort of short selective guide to an enormous and diverse literature on learning processes in economics. We argue that learning is an ubiquitous characteristic of most economic and social systems but it acquires even greater importance in explicitly evolutionary environments where: a) heterogeneous agents systematically display various forms of "bounded rationality"; b) there is a persistent appearance of novelties, both as exogenous shocks and as the result of technological, behavioural and organisational innovations by the agents themselves; c) markets (and other interaction arrangements) perform as selection mechanisms; d) aggregate regularities are primarily emergent properties stemming from out-of-equilibrium interactions. We present, by means of examples, the most important classes of learning models, trying to show their links and differences, and setting them against a sort of ideal framework of "what one would like to understand about learning...". We put a signifiphasis on learning models in their bare-bone formal structure, but we also refer to the (generally richer) non-formal theorising about the same objects. This allows us to provide an easier mapping of a wide and largely unexplored research agenda.Learning, Evolutionary Environments, Economic Theory, Rationality

Qualitative Inquiry in an Age of Educationalese

In this introduction we reflect on two key questions that initiated this special issue on qualitative inquiry: What can qualitative researchers do to regain their post-paradigm-wars cache? How do we avoid distracting “science wars” in the future? We suggest that the strong tendency to narrow the research methods accepted as “scientific” – because they adopt quantitative perspectives and are presumed a priori to be more rigorous – has created an educationalese, a narrative of rigid categories that has not necessarily contributed to more effective or persuasive educational research. The article ends by suggesting that the use of “knowledge mobilization” strategies would help to strengthen qualitative research and educational research in general

Development of INoSIT (Integration Nature of Science in Inquiry with Technology) Learning Models to Improve Science Literacy: A Preliminary studies

Has successfully created the INoSIT learning paradigm to increase students' science literacy competency. This design aims to integrate information and communication technology (ICT) with inquiry and nature of science (NoS) models to teach scientific literacy to junior high school students using a multi-representation method. The BSCS 5E model (Involvement of Biological Science Curriculum Study, Exploration, Explanation, Elaboration, and Evaluation) and the IBL model (Investigation-based learning) have many phases whose implementation requires many processes. So, the INoSIT model is designed to simplify multiple phases or sub-phases. As a result, IBL (inquiry-based learning) is ineffective and inefficient in terms of learning time. It is also challenging to teach scientific literacy of abstract concepts using this method. The study employs a descriptive analysis method in conjunction with a literature review pattern.  The INoSIT model with the syntax Eliciting, Hypothesis, Testing Hypothesis, Elucidation, and Reflection was created from the results of the investigation of the weaknesses of the BSCS 5E (Biological Science Curriculum Study Engagement, Exploration, Explanation, Elaboration, and Evaluation) and the IBL (Inquiry-based learning) models. To construct students' knowledge of literacy and the study is anticipated to contribute to creativity, originality, and the development of a proclivity for inquiry and researc

The Empire Strikes Back: The end of Agile as we know it?

Agile methods have co-evolved with the onset of rapid change in software and systems development and the methodologies and process models designed to guide them. Conceived from the lessons of practice, Agile methods brought a balanced perspective between the intentions of the stakeholder, the management function, and developers. As an evolutionary progression, trends towards rapid continuous delivery have witnessed the advent of DevOps where advances in tooling, technologies, and the environment of both development and consumption exert a new dynamic into the Agile oeuvre. We investigate the progression from Agile to DevOps from a Critical Social Theoretic perspective to examine a paradox in agility – does an always-on conceptualization of production forestall and impinge upon the processes of reflection and renewal that are also endemic to Agile methods? This paper is offered as a catalyst for critical examination of and as a call to action to advocate for sustaining and nurturing reflective practice in Agile and post-Agile methods, such as DevOps. Under threat of disenfranchisement and relegation to automation, we question how evolution towards DevOps may alter key elements in the tenets and principles of the Agile methods phenomenon

Qualitative Marketing Research: The State of Journal Publications

Qualitative methods in marketing have become essential not only for their classical advantage in consumer behavior, but also for their benefits in dealing with big data and data Qualitative methods in marketing have become essential not only for their classical advantage in consumer behavior, but also for their benefits in dealing with big data and data mining. Research from International Data Corporation (IDC) shows that when it comes to online data, unstructured content accounts for 90% of all digital information. Under these circumstances, this study provides a literature review and analysis on the role and relation of qualitative methods with quantitative methods in marketing research. The paper analyzes research articles that include qualitative studies in the top marketing journals during the last decade and focuses on their topic, domain, methods used and whether they used any triangulation with quantitative methods. Starting from this analysis, the study provides recommendations that can help better integrate qualitative methods in marketing research, academics and practice.mining. Research from International Data Corporation (IDC) shows that when it comes to online data, unstructured content accounts for 90% of all digital information. Under these circumstances, this study provides a literature review and analysis on the role and relation of qualitative methods with quantitative methods in marketing research. The paper analyzes research articles that include qualitative studies in the top marketing journals during the last decade and focuses on their topic, domain, methods used and whether they used any triangulation with quantitative methods. Starting from this analysis, the study provides recommendations that can help better integrate qualitative methods in marketing research, academics and practice

The Effectiveness of University Technology Transfer: Lessons Learned from Qualitative and Quantitative Research in the U.S. and U.K.

In recent years, there have been numerous studies of the effectiveness of university technology transfer. Such technology transfer mechanisms include licensing agreements between the university and private firms, science parks, incubators, and university-based startups. We review and synthesize these papers and present some pointed recommendations on how to enhance effectiveness. Implementation of these recommendations will depend on the mechanisms that universities choose to stress, based on their technology transfer "strategy." For example, institutions that emphasize the entrepreneurial dimension of technology transfer must address skill deficiencies in technology transfer offices, reward systems that are inconsistent with enhanced entrepreneurial activity and the lack of training for faculty members, post-docs, and graduate students in starting new ventures or interacting with entrepreneurs. We conjecture that business schools are best positioned to address these skill and educational deficiencies through the delivery of targeted programs to technology licensing officers and members of the campus community wishing to launch startup firms.

Complexity as an empirical tendency: promoting non-measurement as a means to enhanced understanding

In this conceptual paper, I seek to provide an organising framework for conducting qualitative research in complexity studies in management. Building upon the underlying logic of Kauffman's NK(C) model and the notion of second-order complexity, I urge management researchers interested in complex adaptive systems to capture, understand, and articulate complexity as an empirical tendency as opposed to the measurement-driven orientation of many scholars. I contend that the latter orientation's illusion for numerical precision, predictive accuracy and generalizable truthfulness is not only undoable but also unnecessary in the context of providing practically meaningful and realistic recommendations to those interested in complexity