Search results

This chapter examines the case of threshold concepts, as an example of a theory being developed and applied within higher education research. It traces the origins and meaning of the term, reviews its application by higher education researchers and discusses the issues it raises and the critiques it has attracted. This case is of particular interest, as the idea of threshold concepts is little more than a decade old, yet in that time it has attracted considerable attention.

This chapter explores the potential of grounded theory research methods for eliciting threshold concepts. It begins with an overview of threshold concept theory, then reviews current methodological approaches, as well as challenges encountered, when researching threshold concepts. The discussion argues for the suitability of grounded theory for this purpose, using a specific case for illustration. Specific elements of the research design that strengthened the use of grounded theory in the exploration of threshold concepts are described. The case example used is of graduate students and practicing professionals’ learning experiences when acquiring expertise in the online environment. The case is used to demonstrate the grounded theory method’s efficacy for eliciting evidence of transformative learning experiences, leading to implications for improving curriculum design.

This article explores the neglected issue of the overrepresentation in the child protection system of children from ethnic, cultural, religious, racial, and linguistic minorities. It focuses on the accommodation of children’s diverse backgrounds within the s 31(2) threshold and s1 “best interests” stages of intervention under the Children Act 1989. First, it introduces the ethnic child protection penalty as a new tool for capturing the complex nature of overrepresentation of these children. Second, it proposes a framework for understanding the judicial approach in higher court decisions on the current extent and nature of accommodation. Third, it employs the penalty concept to help explain why case law analysis reveals difficulties with the current factor-based approach, whereas empirical research suggests generally satisfactory accommodation in practice. It concludes by proposing a contextualized framework for decision-making in relation to child protection.

This study examines the effects of narcissism and bonus-based incentive plans on managerial decision-making performance. Using an experiment, the authors first examine decision choices under two levels of an incentive threshold (high and low). Narcissism is measured using the Narcissistic Personality Inventory (NPI). Typically, the NPI is used as a single monolithic construct in analyses; however, in this study, the authors subdivide it in two ways to gain more nuanced information about its impact on decision making. First, the authors split the NPI into three levels – high, medium, and low (Hascalovitz & Obhi, 2015), and then decompose it into its adaptive and maladaptive components (Campbell, Hoffman, Campbell, & Marchisio, 2011) to examine how these subdivisions affect performance. Results show that the different levels of incentive thresholds affect performance among narcissistic individuals. Results indicate that individuals higher in narcissism and higher in levels of adaptive and maladaptive narcissism outperform their low-trait counterparts in a lower-threshold environment, but not in a high threshold environment.

Entrepreneurs make a significant contribution to the health of any economy and higher education is regarded as pivotal in efforts to grow entrepreneurial talent. Entrepreneurship education has grown rapidly; yet, there is still controversy over the best way to educate and assess students. This chapter presents a study gathering a consensus of entrepreneur opinion on the concepts critical to thinking as an entrepreneur, in order to inform entrepreneurship curriculum development. There is a general lack of entrepreneurship education research that integrates the external stakeholder perspective in this way.

Using a Delphi-style method with twelve entrepreneurs, five candidate entrepreneurship threshold concepts are identified. Threshold concepts have a powerfully transformative effect on the learner, and important integrative qualities, allowing the learner to make the sense of previously isolated pockets of knowledge. A ‘new world-view’ or episteme can be constructed – a kind of disciplinary thinking, peculiar in this case, to entrepreneurs.

This chapter contributes to the call for more research grounded discussion on the quality and effectiveness of entrepreneurship education initiatives. Designing curricula around the threshold concepts in entrepreneurship will enable educators to offer particular support in areas where students are likely to get ‘stuck’ and will facilitate constructive alignment with assessment.

This chapter offers a conceptual perspective of what students need to understand to understand entrepreneurship, and educators’ views on how best to educate students in it, in response to calls for a greater understanding of the learning environment. The research uses the lens of the threshold concept framework to inform a conceptual approach to entrepreneurship education. The threshold concept framework posits that in any academic discipline there are concepts that have a particularly transformative effect on student learning representing a transformed way of understanding something, without which the learner cannot progress.

Research was undertaken in three stages to identify what is distinctive about thinking like an entrepreneur, how to educate students to think like entrepreneurs and how students understand thinking like entrepreneurs. The first and second stages of the study are the focus of this chapter. Candidate threshold concepts in entrepreneurship and educators’ perspectives of effective ways to educate students in entrepreneurship are presented.

Data from 11 individual and group semi-structured interviews conducted with 18 entrepreneurship educators in 10 higher education institutions across the UK was integrated with findings from a Delphi survey with 10 expert entrepreneurs.

By offering the perspectives of entrepreneurship educators and entrepreneurs, this chapter makes a valuable contribution to a conceptually grounded and innovative approach to entrepreneurship education.

This survey focuses on two families of nonlinear vector time series models, the family of vector threshold regression (VTR) models and that of vector smooth transition regression (VSTR) models. These two model classes contain incomplete models in the sense that strongly exogeneous variables are allowed in the equations. The emphasis is on stationary models, but the considerations also include nonstationary VTR and VSTR models with cointegrated variables. Model specification, estimation and evaluation is considered, and the use of the models illustrated by macroeconomic examples from the literature.

Responses to minimum income and minimum spending questions are used to produce economic well-being thresholds. Thresholds are estimated using a regression framework. Regression coefficients are based on U.S. Survey of Income and Program Participation (SIPP) data and then applied to U.S. Consumer Expenditure Survey (CE) data. Three different resource measures are compared to the estimated thresholds. The first resource measure is total before-tax money income, and the other two are expenditure based. The first of these two refers to expenditure outlays and the second to outlays adjusted for the value of the service flow of owner-occupied housing (rental equivalence). The income comparison is based on SIPP data while the outlays comparisons are based on CE data. Results using official poverty thresholds are shown for comparison. This is among the earliest work in the U.S. in which expenditure outlays have been used for economic well-being determinations in combination with personal assessments, and the first time rental equivalence has been used in such an exercise. Comparisons of expenditures for various bundles of commodities are compared to the CE derived thresholds to provide insight concerning what might be considered minimum or basic.

Results reveal that CE and SIPP MIQ thresholds are higher than MSQ thresholds, and resulting poverty rates are also higher with the MIQ. CE-based MSQ thresholds are not statistically different from average expenditure outlays for food, apparel, and shelter and utilities for primary residences. When reported rental equivalences for primary residences that are owner occupied are substituted for out-of-pocket shelter expenditures, single elderly are less likely to be as badly off as they would be with a strict outlays approach in defining resources.

In this chapter, we examine the impact of pay-for-performance incentives on learning-by-doing. We exploit personnel data on fruit pickers paid under two distinct compensation contracts: a standard piece rate plan and one with an extra one-time bonus tied to output. Under the latter, we observe bunching of performance just above the bonus threshold, suggesting workers distort their behavior in response to the discrete bonus. Such bunching behavior increases as workers gain experience. At the same time, the bonus contract induces considerable learning-by-doing for workers throughout the productivity distribution who presumably hope to one day hit the target, and these improvements significantly outweigh the losses to the firm from the bunching. In contrast, under the standard piece rate contract, we find minimal evidence of bunching and only small performance improvements at the bottom of the productivity distribution. Our results suggest that contract design can help foster learning on the job, underscoring the importance of dynamic considerations in principle-agent models.

The authors derive a risk lower bound in estimating the threshold parameter without knowing whether the threshold regression model is continuous or not. The bound goes to zero as the sample size n grows only at the cube-root rate. Motivated by this finding, the authors develop a continuity test for the threshold regression model and a bootstrap to compute its p-values. The validity of the bootstrap is established, and its finite-sample property is explored through Monte Carlo simulations.