In author name disambiguation, author forenames are used to decide which name instances are disambiguated together and how much they are likely to refer to the same author. Despite such a crucial role of forenames, their effect on the performance of heuristic (string matching) and algorithmic disambiguation is not well understood. This study assesses the contributions of forenames in author name disambiguation using multiple labeled data sets under varying ratios and lengths of full forenames, reflecting real-world scenarios in which an author is represented by forename variants (synonym) and some authors share the same forenames (homonym). The results show that increasing the ratios of full forenames substantially improves both heuristic and machine-learning-based disambiguation. Performance gains by algorithmic disambiguation are pronounced when many forenames are initialized or homonyms are prevalent. As the ratios of full forenames increase, however, they become marginal compared to those by string matching. Using a small portion of forename strings does not reduce much the performances of both heuristic and algorithmic disambiguation methods compared to using full-length strings. These findings provide practical suggestions, such as restoring initialized forenames into a full-string format via record linkage for improved disambiguation performances. © 2019 ASIS&T

Introduction Recent work reveals a new source of error in number line estimation (NLE), theleft digit effect(Lai, Zax, et al., 2018), whereby numerals with different leftmost digits but similar magnitudes (e.g., 399, 401) are placed farther apart on a number line (e.g., 0 to 1,000) than is warranted. The goals of the present study were to: (1) replicate the left digit effect, and (2) assess whether it is related to mathematical achievement. Method Participants were all individuals (adult college students) who completed the NLE task in the laboratory between 2014 and 2019 for whom SAT scores were available (n = 227). Results We replicated the left digit effect but found its size was not correlated with SAT math score, although it was negatively correlated with SAT verbal score for one NLE task version. Conclusions These findings provide further evidence that individual digits strongly influence estimation performance and suggest that this effect may have different cognitive contributors, and predict different complex skills, than overall NLE accuracy.

This study discusses the development of a basic electronics knowledge (BEK) assessment as a pretest activity for undergraduate students in engineering and related fields. The 28 BEK items represent 12 key concepts, including properties of serial circuits, knowledge of electrical laws (e.g., Kirchhoff's and Ohm's laws), and properties of digital multimeters. This paper first discusses a psychometric evaluation of the BEK assessment to understand its basic measurement properties and to examine various group-level differences based on demographic, institutional, and instructor characteristics. Subsequently, the relationship between BEK scores on the 23 retained items and performance on an existing complex collaborative simulation-based electronics task is discussed. Results demonstrated that basic content knowledge alone may not be sufficient for students to demonstrate knowledge of electronics skills on more complex tasks. The research also carries great importance given ongoing concerns about improving the overall state and diversity of the engineering workforce and its associated pipeline to meet the demands of the national economy. © 2020 Educational Testing Service

Whether creativity is a domain-general or domain-specific ability has been a topic of intense speculation. Although previous studies have examined domain-specific mechanisms of creative performance, little is known about commonalities and distinctions in neural correlates across different domains. We applied activation likelihood estimation (ALE) meta-analysis to identify the brain activation of domain-mechanisms by synthesizing functional neuroimaging studies across three forms of artistic creativity: music improvisation, drawing, and literary creativity. ALE meta-analysis yielded a domain-general pattern across three artistic forms, with overlapping clusters in the presupplementary motor area (pre-SMA), left dorsolateral prefrontal cortex, and right inferior frontal gyrus (IFG). Regarding domain-specificity, musical creativity was associated with recruitment of the SMA-proper, bilateral IFG, left precentral gyrus, and left middle frontal gyrus (MFG) compared to the other two artistic forms; drawing creativity recruited the left fusiform gyrus, left precuneus, right parahippocampal gyrus, and right MFG compared to musical creativity; and literary creativity recruited the left angular gyrus and right lingual gyrus compared to musical creativity. Contrasting drawing and literary creativity revealed no significant differences in neural activation, suggesting that these domains may rely on a common neurocognitive system. Overall, these findings reveal a central, domain-general system for artistic creativity, but with each domain relying to some degree on domain-specific neural circuits.

Background Project-based learning has shown promise in improving learning outcomes for diverse students. However, studies on its impacts have largely focused on the perceptions of students and instructors or students' immediate performance. This study reports the impact of taking a project-based introductory engineering course on students' subsequent academic success. Purpose/Hypothesis This quantitative study examines characteristics related to enrollment in the project-based introductory engineering course and subsequent academic performance. We hypothesized that participation in the course would be associated with higher academic performance in subsequent engineering courses. In addition, we examined heterogeneity effects for students traditionally underrepresented in engineering education. Design/Method This study utilized data on students' demographics, academic preparation, course enrollment, and course performance from 1,318 engineering students from a large public university in Southern California. Logistic regression analysis with robust standard errors examined enrollment patterns. We applied propensity scores as inverse-probability weights in multiple linear models to calculate the average treatment effect on the treated for participants from the project-based introductory engineering course in five subsequent engineering courses. This analysis was conducted for all students and for selected student subgroups. Results Enrollment in the project-based introductory engineering course was positively associated with students' performance in some subsequent engineering courses and did not adversely affect students traditionally underrepresented in engineering. Conclusions This study provides an example of a project-based introductory engineering course that can support students' academic success in engineering. The benefits detected for some student populations (e.g., female) are encouraging for broadening engineering pathways.

Background To address social disparities and generate an innovative workforce, engineering higher education should provide learning environments that benefit students from all backgrounds. However, because engineering programs are not enrolling or retaining women of color at demographic parity, a better understanding of these students' experiences is needed to develop effective interventions. Purpose This study analyzes research on women of color in undergraduate engineering education to determine what influences their experiences, participation, and advancement. We identify challenges to and strategies for persistence and present recommendations for engineering institutions to create interventions that support women of color and mitigate institutional inequities. Scope/Method Using the snowballing method, we identified 65 empirical studies published between 1999 and 2015 that met the criteria for this review. These studies represented qualitative, mixed-methods, and quantitative methodologies from various fields. We conducted a systematic thematic synthesis, informed by frames of intersectionality, critical race theory, and community cultural wealth. Conclusions Women of color use navigational strategies to address the social pain of race and gender inequity in engineering education. Institutions should take responsibility for generating a sense of belonging for women of color and provide social and structural supports that increase self-efficacy, address social pain, and improve retention.

Collaborative inquiry learning affords educators a context within which to support understanding of scientific practices, disciplinary core ideas, and crosscutting concepts. One approach to supporting collaborative science inquiry is through problem-based learning (PBL). However, there are two key challenges in scaffolding collaborative inquiry learning in technology rich environments. First, it is unclear how we might understand the impact of scaffolds that address multiple functions (e.g., to support inquiry and argumentation). Second, scaffolds take different forms, further complicating how to coordinate the forms and functions of scaffolds to support effective collaborative inquiry. To address these issues, we identify two functions that needed to be scaffolded, the PBL inquiry cycle and accountable talk. We then designed predefined hard scaffolds and just-in-time soft scaffolds that target the regulation of collaborative inquiry processes and accountable talk. Drawing on a mixed method approach, we examine how middle school students from a rural school engaged with Crystal Island: EcoJourneys for two weeks (N=45). Findings indicate that hard scaffolds targeting the PBL inquiry process and soft scaffolds that targeted accountable talk fostered engagement in these processes. Although the one-to-one mapping between form and function generated positive results, additional soft scaffolds were also needed for effective engagement in collaborative inquiry and that these soft scaffolds were often contingent on hard scaffolds. Our findings have implications for how we might design the form of scaffolds across multiple functions in game-based learning environments.

This study develops a framework to conceptualize the use and evolution of machine learning (ML) in science assessment. We systematically reviewed 47 studies that applied ML in science assessment and classified them into five categories: (a) constructed response, (b) essay, (c) simulation, (d) educational game, and (e) inter-discipline. We compared the ML-based and conventional science assessments and extracted 12 critical characteristics to map three variables in a three-dimensional framework:construct,functionality, andautomaticity. The 12 characteristics used to construct a profile for ML-based science assessments for each article were further analyzed by a two-step cluster analysis. The clusters identified for each variable were summarized into four levels to illustrate the evolution of each. We further conducted cluster analysis to identify four classes of assessment across the three variables. Based on the analysis, we conclude that ML has transformed-but notyetredefined-conventional science assessment practice in terms of fundamental purpose, the nature of the science assessment, and the relevant assessment challenges. Along with the three-dimensional framework, we propose five anticipated trends for incorporating ML in science assessment practice for future studies: addressing developmental cognition, changing the process of educational decision making, personalized science learning, borrowing 'good' to advance 'good', and integrating knowledge from other disciplines into science assessment.

Word learning is a social act. Because there is an arbitrary relation between words and their meaning, children must learn words from other people. Other people, however, are not always reliable sources of knowledge. People can be ignorant, hold false beliefs, or simply be deceptive. How do children evaluate the reliability of sources of knowledge for word learning? This chapter investigates the possibility that children possess multiple mechanisms for evaluating such reliability and possess such mechanisms very early in development. We suggest that infants not only track the accuracy of others using statistical learning mechanisms but also incorporate their existing knowledge of the world into judgments of reliability to make judicious inferences about the knowledge of a speaker and the pragmatics of a communicative act. Moreover, we suggest that as children get older, both low-level associative mechanisms and higher-level cognitive processes influence the way in which children track and use others’ reliability as sources of knowledge. (PsycInfo Database Record (c) 2022 APA, all rights reserved)