4 research outputs found

    A process model for developing learning design patterns with international scope

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    This paper investigates the process of identifying design patterns in international collaborative learning environments. In this context, design patterns are referred to as structured descriptions of best practice with pre-defined sections such as problem, solution and consequences. We pay special attention to how the scope of a design pattern is identified and articulated. Based on a review of the seminal design patterns literature and current practice in the area of learning design, the lack of a more specific process description for developing patterns with international scope is identified. The paper suggests a process model for developing patterns with international scope. This model is exemplified in a case study that links the analysis of observation in international learning environments to the articulation of design patterns by identifying culturally independent core values that constitute the foundations of a design pattern with international scope. These core values are linked to recurrent learning behaviors and specific artefacts that support learning in the articulation of a design pattern. The findings contribute to gaining a deeper understanding of the pattern scoping and abstraction process in international learning environments

    Social media and sensemaking patterns in new product development: demystifying the customer sentiment

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    Artificial intelligence by principle is developed to assist but also support decision making processes. In our study, we explore how information retrieved from social media can assist decision-making processes for new product development (NPD). We focus on consumers’ emotions that are expressed through social media and analyse the variations of their sentiments in all the stages of NPD. We collect data from Twitter that reveal consumers’ appreciation of aspects of the design of a newly launched model of an innovative automotive company. We adopt the sensemaking approach coupled with the use of fuzzy logic for text mining. This combinatory methodological approach enables us to retrieve consensus from the data and to explore the variations of sentiments of the customers about the product and define the polarity of these emotions for each of the NPD stages. The analysis identifies sensemaking patterns in Twitter data and explains the NPD process and the associated steps where the social interactions from customers can have an iterative role. We conclude the paper by outlining an agenda for future research in the NPD process and the role of the customer opinion through sensemaking mechanisms

    Towards Understanding How to Assess Help-Seeking Behavior Across Cultures

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    In recent years, there has been increasing interest in automatically assessing help seeking, the process of referring to resources outside of oneself to accomplish a task or solve a problem. Research in the United States has shown that specific help-seeking behaviors led to better learning within intelligent tutoring systems. However, intelligent tutors are used differently by students in different countries, raising the question of whether the same help-seeking behaviors are effective and desirable in different cultural settings. To investigate this question, models connecting help-seeking behaviors with learning were generated from datasets from students in three countries – Costa Rica, the Philippines, and the United States, as well as a combined dataset from all three sites. Each model was tested on data from the other countries. This study found that models of effective help seeking transfer to some degree between the United States and Philippines, but not between those countries and Costa Rica. Differences may be explained by variations in classroom practices between the sites; for example, greater collaboration observed in the Costa Rican site indicates that much help seeking occurred outside of the technology. Findings indicate that greater care should be taken when assuming that the models underlying AIED systems generalize across cultures and contexts
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