An Exploratory Study of Lecturers' Views of Out-of-class Academic Collaboration Among Students

This article reports an exploratory study of lecturers' perceptions of out-of-class academic collaboration (OCAC) among students at a large Singapore university. Two types of OCAC were investigated: collaboration initiated by students, e.g., groups decide on their own to meet to prepare for exams, and collaboration required by teachers, e.g., teachers assign students to do projects in groups. Data were collected via one-on-one interviews with 18 faculty members from four faculties at the university. Findings suggest that OCAC, especially of a teacher-required kind, is fairly common at the university. Faculty members' views on factors affecting the success of OCAC are discussed for the light they might shed on practices to enhance the effectiveness of OCAC

Exploratory landscape metrics for agricultural sustainability

Socioeconomic growth and urban change have been an increasing concern for decision makers in recent decades. The monitoring, mapping, and analysis of agricultural land use change, especially in areas where urban change has been high, is crucial. The collision between traditional economic activities related to agriculture in tourist areas such as the Algarve and current demand for tourism infrastructures in urban regions is also leading to loss of economic activity. This article uses a combined geographical information system approach with CORINE land cover datasets to perform a Shannon’s diversity index quantifying changes in agricultural areas. The article then expands on the nature of the agricultural changes observed, and offers a multi-temporal assessment by means of landscape metrics in order to understand the shifting land use patterns for the Algarve in land use planning and regional economic equilibrium: a) forest regions become transformed into agricultural areas and agricultural areas become urban; b) areas that are initially agricultural become scattered residential regions created by economic investors; and c) agricultural land use changes have a cyclical nature in which—in the course of the economic recession—such dynamic effects brought about a decrease in tourism and focus on traditional sectors

The mediation between participative leadership and employee exploratory innovation: Examining intermediate knowledge mechanisms

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.We examine mediation effects of coworker knowledge sharing and absorptive capacity on the participative leadership–employee exploratory innovation relationship in R&D units of Taiwanese technology firms. Deploying a time-lagged questionnaire method implemented over four business quarters, data is generated from 1600 paired samples (managers and employees) in R&D units of Taiwanese technology firms. The structural equation modeling results reveal that (1) participative leadership is positively related to employee exploratory innovation; (2) coworker knowledge and (3) absorptive capacity partially mediate the relationship between participative leadership and employee exploratory innovation independently; and, (4) coworker knowledge sharing in combination with absorptive capacity partially mediates this relationship. The results extend previous research on participative leadership and innovation by demonstrating that participative leadership is related to employee exploratory innovation (Lee and Meyer-Doyle, 2017; Mom et al., 2009).Results also confirm that participative leadership drives employee exploratory innovation through employee absorptive capacity. This reinforces the need highlighted by Lane et al. (2006) to investigate the role of absorptive capacity at the individual-level. Collectively, while participative leadership is important for employee exploratory innovation it is the knowledge mechanisms existing and interacting at the employee-level that are central to generating increased employee exploratory innovation from this leadership approach

Managing exploratory innovation

Although the concept of exploration has been widely used in management research since James March's seminal article, the literature on exploration remains rather fuzzy. The question of exploration is dominated by the literature on ambidexterity but this research actually says little about concretely managing exploratory innovation itself, although this appears to be a central concern of most industrial firms today. Based on a material (twenty presentations made in a research seminar the authors have organized in the last two years) and a critical review of the literature, this paper provides new theoretical and managerial insights on the management of exploratory innovation. We first identify three complementary perspectives: 1. Managing knowledge for exploration, 2. Organizing for exploration, and 3. Creating new value spaces. Secondly, we recommend focusing the management of exploratory innovation on the following two processes: identifying an exploratory field, creating new opportunities via experimentation.Exploration, management of innovation, knowledge, value spaces

Exploration through drawings in the conceptual stages of product design

This paper argues that sequences of exploratory drawings - constructed by designer's movements and decisions - trace systematic and logical paths from ideas to designs. This argument has three parts. First, sequences of exploratory sketches produced by product designers, against the same task specification, are analyzed in terms of the cognitive categories of reinterpretation, emergence and abstraction. Second, a computational model is outlined for the process of exploration through drawing and third the model is applied to elucidate the logic in the sequences of exploratory sketches examined earlier

Sparse Exploratory Factor Analysis

Sparse principal component analysis is a very active research area in the last decade. It produces component loadings with many zero entries which facilitates their interpretation and helps avoid redundant variables. The classic factor analysis is another popular dimension reduction technique which shares similar interpretation problems and could greatly benefit from sparse solutions. Unfortunately, there are very few works considering sparse versions of the classic factor analysis. Our goal is to contribute further in this direction. We revisit the most popular procedures for exploratory factor analysis, maximum likelihood and least squares. Sparse factor loadings are obtained for them by, first, adopting a special reparameterization and, second, by introducing additional [Formula: see text]-norm penalties into the standard factor analysis problems. As a result, we propose sparse versions of the major factor analysis procedures. We illustrate the developed algorithms on well-known psychometric problems. Our sparse solutions are critically compared to ones obtained by other existing methods