Using Concept MappingPattern Matching to Develop a Conceptual Framework for Successful Transition of First Year Saudi Students into Postsecondary Education

This study identified the future ideal functions of PYP and developed a conceptual framework for the program at King Saud University. Four research questions were answered in this study including: 1) Using the Concept Mapping/Pattern Matching methodology, how do Saudi male and female postsecondary stakeholders conceptualize the future ideal functions of Preparatory Year Deanship to help students successfully transition into their first year of college/university?; 2) Does this Concept Mapping/Pattern Matching conceptualization compare and contrast with the current working model of the Preparatory Year Program at King Saud University?; 3) Does this Concept Mapping/Pattern Matching conceptualization compare and contrast with King Saud University\u27s explicit strategic plan?; and 4) When conducting a Concept Mapping/Pattern Matching conceptualization, how do the results for males compare and contrast with the results for females?;The Concept Mapping/Pattern Matching methodology advanced by (Trochim 1989a, 1989b; Kane & Trochim, 2007) utilized for data collection and analyzing. Fourteen male including 2-PYP students, 1-Medicine College Faculty, 1-Business Administration College Faculty, 1-Engineering College Faculty, 4-PYP Faculty, 1-Academic Advising Faculty at PYP, 1-Students Affairs Faculty at KSU, 1- Students Affairs at PYP, and 2-Educational Company and nine female including 3-PYP\u27 students, 1- Pharmacy College Faculty, 2-PYP Faculty, 2-Parents, and 1-Educational Company participated in two separate brainstorming sessions. The male participants generated 48 statements and the female group generated 36 statements. The participants in each group sorted the generating statements individually into groups and rated them based on a five-point scale for relative importance and institutional efficacy.;For each group male/female the Multidimensional Scaling and Hierarchical Cluster Analysis were conducted to create various concept maps, the final one being a seven-cluster and six-cluster concept map for male and female, respectively, representing the stakeholders\u27 conceptualization of the field being studied. Following the creation of the concept maps for each group, the resulting priorities and their conceptualization schema were both compared and contrasted to the current working model of PYP and the explicit strategic plan of KSU (KSU2030) for similarities and differences in a qualitative document analysis. The male and female perceptions were also compared and contrasted.;The study revealed three main dimensions for developing PYP at KSU including Organizational design and structure, Pedagogical functionality, and Student services. Further, seven foundational principles may be embraced to develop the three dimensions previously mentioned including: 1) adopting a talent philosophy to first meet student\u27s needs and then the institution\u27s mission; 2) a flexible PYP model to meet individual student\u27s needs; (3) applying a pedagogical on theory-based; (4) reorganizing PYP\u27s tasks and centralizing student\u27s services; (5) involving KSU\u27s colleges; (6) supporting non- filtering program; and (7) adopting self-operation. The significance of this study for the educational policymaker, planner, and developer, is that the findings can be used as a model to make student\u27s transition into postsecondary education successful

Fixing feedback revision rules in online markets

Feedback withdrawal mechanisms in online markets aim to facilitate the resolution of conflicts during transactions. Yet, frequently used online feedback withdrawal rules are flawed and may backfire by inviting strategic transaction and feedback behavior. Our laboratory experiment shows how a small change in the design of feedback withdrawal rules, allowing unilateral rather than mutual withdrawal, can both reduce incentives for strategic gaming and improve coordination of expectations. This leads to less trading risk, more cooperation, and higher market efficiency.Series: Department of Strategy and Innovation Working Paper Serie

The cognitive construction of programs by novice programmers : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University

Human memory and cognition are studied to aid novice programmers with the cognitive construction and the acquisition of program plans. Particular emphasis is placed on the storage and retrieval of program knowledge, the cognitive structure of stored program knowledge, the effects of transferring cognitive structures from one programming language to another, and the learning activities involved with learning a new programming language. Cognitive principles are applied to the design of a programming language and environment. The design of both the programming language and environment are discussed together with an introduction of how they are used. The hypothetical results of two experiments are argued to demonstrate that the programming language and environment are well suited in supporting the development of program plans

Strategic Wage Bargaining, Labor Market Volatility, and Persistence

This paper modifies the standard Mortensen-Pissarides model in order to explain the cyclical behavior of vacancies and unemployment. The modifications include strategic wage bargaining and convex labor adjustment costs. We find that this setup replicates the cyclical behavior of both labor market variables remarkably well. First, we show that the model with strategic wage bargaining matches closely the volatility of vacancies and unemployment. Second, the introduction of convex labor adjustment costs makes both variables much more persistent. Third, our analysis indicates that these two modifications are complementary in generating labor market volatility and persistence.Business Cycles, Matching, Strategic Bargaining, Vacancy Persistence

Strategic Wage Bargaining, Labor Market Volatility, and Persistence

This paper modifies the standard Mortensen-Pissarides job matching model in order to explain the cyclical behavior of vacancies and unemployment. The modifications include strategic wage bargaining (Hall and Milgrom, 2006) and convex labor adjustment costs. The results reveal that our model replicates the cyclical behavior of both variables remarkably well. First, we show that strategic wage bargaining increases the volatility of vacancies and unemployment enormously. Second, the introduction of convex labor adjustment costs makes both variables much more persistent. Third, our analysis indicates that both modifications are complementary in generating volatile and persistent labor market variables.Business Cycles, Matching, Strategic Bargaining

Learning Visual Clothing Style with Heterogeneous Dyadic Co-occurrences

With the rapid proliferation of smart mobile devices, users now take millions of photos every day. These include large numbers of clothing and accessory images. We would like to answer questions like `What outfit goes well with this pair of shoes?' To answer these types of questions, one has to go beyond learning visual similarity and learn a visual notion of compatibility across categories. In this paper, we propose a novel learning framework to help answer these types of questions. The main idea of this framework is to learn a feature transformation from images of items into a latent space that expresses compatibility. For the feature transformation, we use a Siamese Convolutional Neural Network (CNN) architecture, where training examples are pairs of items that are either compatible or incompatible. We model compatibility based on co-occurrence in large-scale user behavior data; in particular co-purchase data from Amazon.com. To learn cross-category fit, we introduce a strategic method to sample training data, where pairs of items are heterogeneous dyads, i.e., the two elements of a pair belong to different high-level categories. While this approach is applicable to a wide variety of settings, we focus on the representative problem of learning compatible clothing style. Our results indicate that the proposed framework is capable of learning semantic information about visual style and is able to generate outfits of clothes, with items from different categories, that go well together.Comment: ICCV 201