Scientific Argumentation as a Foundation for the Design of Inquiry-Based Science Instruction

Despite the attention that inquiry has received in science education research and policy, a coherent means for implementing inquiry in the classroom has been missing [1]. In recent research, scientific argumentation has received increasing attention for its role in science and in science education [2]. In this article, we propose that organizing a unit of instruction around building a scientific argument can bring inquiry practices together in the classroom in a coherent way. We outline a framework for argumentation, focusing on arguments that are central to science—arguments for the best explanation. We then use this framework as the basis for a set of design principles for developing a sequence of inquiry-based learning activities that support students in the construction of a scientific argument. We show that careful analysis of the argument that students are expected to build provides designers with a foundation for selecting resources and designing supports for scientific inquiry. Furthermore, we show that creating multiple opportunities for students to critique and refine their explanations through evidence-based argumentation fosters opportunities for critical thinking, while building science knowledge and knowledge of the nature of science

LEARNING STRATEGIES FOR EFL STUDENTS IN DEVELOPING THEIR VOCABULARY MASTERY

Learning strategies are the deliberate actions that learners select and control to achieve desired goals or academic objectives. In the area of vocabulary mastery, learning strategies can be defined as various ways of all language learners to learn new vocabulary items in accordance with the learners’ needs and preferences. In learning a foreign language, choice of learning strategies is much influenced by or associated with a number of factors such as : language being learned, duration, degree of metacognitive awareness, age, sex, attitudes, personality characteristics, career orientation, language teaching methods, and task requirements. A more effective language learner is the one who uses better learning strategies and implements more appropriate strategies than do less effective learners in each of the main language skills

Developing a Measurement Scale for Cruising Motivations

Although motivation has been extensively studied in the tourism literature, the discussion of motivation has not been expanded to cruise tourism. Following Churchill’s (1979) recommended measurement scale development procedures, this study seeks to develop a measurement scale for cruising motivation. The final scale was deemed to be both reliable and valid. It is suggested that this study will serve as a stepping stone to further investigations on cruising motivations

Inferring Individual Preferences And Latent Behavioral Factors With Incomplete Information

This dissertation extends prior research on inferring individual preferences from the following two aspects: one is to examine important latent behavioral factors affecting consumers\u27 consumption decisions; the other is to overcome the challenges arising from incomplete information. Regarding latent behavioral factors, this dissertation considers the following two aspects: (1) three types of intragroup dynamics behavior, and (2) variety-seeking behavior. Regarding incomplete information, this dissertation focuses on two types of incomplete information: individual\u27s behavior and identity, and order of consumption. Specifically, Chapter 2 presents a method to infer heterogeneous individual preferences and three components of intragroup dynamics using just aggregate and de-identified data. Chapter 3 emphasizes the effect of consumption outcomes on an individual\u27s propensity for variety-seeking when the order of consumption is unobserved. To overcome the challenges arising from incomplete information, this dissertation develops advanced individual-level Bayesian models and uses two-step iterative algorithms to estimate the proposed models in an MCMC framework. In-depth simulation studies show that the parameters are well recovered, suggesting that the proposed models are identified. Furthermore, this dissertation shows that ignoring latent behavioral factors may lead to biased estimation of individual preferences, which could result in many consequences. This dissertation applies the proposed methods to two empirical settings: an individual-level TV viewing and targeted TV advertising setting using Nielsen People Meter (NPM) data, and an online video game environment. In the TV viewing setting, it is shown that the proposed method could significantly improve the efficiency of TV ad targeting through counterfactual analysis. In the video-game environment, results show that although there is extensive heterogeneity, on average, positive consumption outcomes lead to inertial preferences, while negative consumption outcomes lead to variety-seeking. In sum, this dissertation shows the importance to incorporate important latent behavioral factors in inferring heterogeneous individual preferences especially when data are incomplete, and proposes innovative methods to overcome the challenges emerging from incomplete information

E-learning by Time Dynamic Model Using Data Mining

The object of this paper is to build up Just in Time Dynamic Learner Models to analyze learners' behaviors and to evaluate learners' performance in online education systems by using rich data collected from e-learning systems. The goal is to create metrics to measure learners' characteristics from usage data. To achieve this goal we need to use data mining methods, especially clustering algorithms, to second patterns from which metrics can be derived from usage data. In this paper, we propose a six layer models(raw data layer, fact data layer, data mining layer, measurement layer, metrics layer and pedagogical application layer) to create a just in time learner model which draws inferences from usage data. In this approach, we collect raw data from online systems, latter fact data from raw data, and then use clustering mining methods to create measurements and metrics

Inferring User Knowledge Level from Eye Movement Patterns

The acquisition of information and the search interaction process is influenced strongly by a person’s use of their knowledge of the domain and the task. In this paper we show that a user’s level of domain knowledge can be inferred from their interactive search behaviors without considering the content of queries or documents. A technique is presented to model a user’s information acquisition process during search using only measurements of eye movement patterns. In a user study (n=40) of search in the domain of genomics, a representation of the participant’s domain knowledge was constructed using self-ratings of knowledge of genomics-related terms (n=409). Cognitive effort features associated with reading eye movement patterns were calculated for each reading instance during the search tasks. The results show correlations between the cognitive effort due to reading and an individual’s level of domain knowledge. We construct exploratory regression models that suggest it is possible to build models that can make predictions of the user’s level of knowledge based on real-time measurements of eye movement patterns during a task session

The Performance of University Spin-Offs: The Impact of Entrepreneurial Capabilities and Social Networks of Founding Teams during Start-Ups

Objectives: University spin-offs have increasingly received attention from academia, governments, and policymakers because they not only generate new innovations, productivity, and jobs the regional economies but also significantly improve university productivity and creativity (Hayter, 2013, Urbano and Guerrero, 2013). However, a lack of understanding of the contribution made by a founding team to a spin-off’s performance still remains within current studies. Employing a resource-based view theory and social networks approach, this paper addresses this gap by exploring university spin-offs in Spain. Prior work: University spin-off studies have concentrated on analysing entrepreneurial business models (Ndonzuau et al., 2002, Vohora et al., 2004b, Bower, 2003, Mets, 2010) to understand how the commercialization of research is undertaken to create a university spin-off. University spin-offs were also been analysed from the perspective of a university’s capabilities (Powers and McDougall, 2005), or capabilities and social networks of an established spin-off instead of the founding teams (Walter et al., 2006). Moreover, Vohora et al. (2004a) and Shane (2004) have suggested founders need to build capable teams, which must have entrepreneurial capabilities and qualitative social networks, to create effective university spin-offs. Both entrepreneurial capability and social network theory have been studied in prior entrepreneurship research, but have received less attention within the context of the university spin-offs (Gonzalez-Pernia et al., 2013). Approach: Utilising an internet-based survey, this paper explores entrepreneurial capabilities and social networks of founding teams in Spanish university spin-offs using quantitative data analysis. Basing upon resource-based view theory of Barney (1991) to study entrepreneurial capabilities of the founding teams, the research employ entrepreneurial technology, strategy, human capital, organizational viability, and commercial resources (see Vohora et al., 2004a). To study social networks of a founding team, we employ the conceptual model of Hoang and Antoncic (2003) that divides networks into three components: structure, governance, and content. Results and implications: The results from an examination of the sample of 181 Spanish university spin-offs empirically demonstrate that by exploiting social networks a founding team can improve its entrepreneurial capabilities, which in turn enhance its spin-off’s performance. By employing the work of Vohora et al. (2004a) and Shane (2004), this paper constructs a model in which entrepreneurial capabilities play a mediate role between social networks and spin-off’s performance. Thus, the paper has implications for universities in training and policy development to support spin-off’s activity. Value: This study addresses some fundamental questions to contribute to the theory-based understanding of university spin-offs: How do entrepreneurial capabilities of founding teams influence the performance of university spin-offs? How do social networks of founding teams contribute to the process of the university spin-offs

Process Tracing: From Philosophical Roots to Best Practices (SWP 21)

This paper has two overarching goals – to summarize recent developments on the philosophical and practical dimensions of process tracing, and to identify features common to best practices of it on different kinds of arguments, with different kinds of available evidence, in different substantive research domains. First, we define process tracing and discuss its foundations in the philosophy of social science. Next, we address its techniques and evidentiary sources, and advance ten criteria for judging its quality in particular pieces of research. Finally, we analyze the methodological issues specific to process tracing on general categories of theories, including structural-institutional, cognitive-psychological, and sociological.&nbsp