Universal and Specific Services for University Students with Specific Learning Disabilities: The Relation to Study Approach,Academic Achievement,and Satisfaction

In recent years, an increasing number of students with specific learning disabilities (SLDs) have enrolled in universities. The present exploratory study examined the frequency of use and appreciation of universal (open to every student) and specific services (offered to students with SLDs) and their relation to age, academic achievement, satisfaction, self-efficacy, and use of self-regulated learning (SRL) strategies. Participants were 147 Italian university students with SLD diagnoses (42 males; mean age: 22.49, SD = 3.29). Results showed that, overall, the frequency of use and appreciation of specific services were positively related to academic satisfaction, self-efficacy, and SRL strategies. Furthermore, frequency of use of compensatory tools and dispensatory measures was positively associated with academic achievement. These findings suggest that universities play an important role in supporting students with SLDs during their academic years by providing them with useful services and accommodations.     

Important Considerations for Assessment to Function in the Service of Education

Professor Gordon argues for a significant reorientation in the focus and impact of assessment in education. For the types of assessment activities that he advocates to prosper and positively impact education, serious attention must be paid to two important topics: (1) the conceptual underpinnings of the assessment practices we develop and use to support learning and instruction, and (2) the arguments and evidence we establish for their validity given the intended interpretive use. Such a focus highlights fundamental concepts that have long existed in the broader assessment literature – carefully defining and operationalizing our constructs and then validating the assessments of those constructs. What differs now are the conceptual frameworks, briefly outlined here, that can and must be used to guide both aspects of such work.     

Strategy selection for cognitive skill acquisition depends on task demands and working memory capacity

The involvement of working memory capacity (WMC) in ruled-based cognitive skill acquisition is well-established, but the duration of its involvement and its role in learning strategy selection are less certain. Participants (N = 610) learned four logic rules, their corresponding symbols, or logic gates, and the appropriate input–output combinations in three-gate circuit patterns. Participants practiced 120 repetitions of each rule (480 total gates) over the course of 10 training blocks. Memory load varied between subjects. The confluence of task demands and individual differences in WMC (N = 518) dramatically affected speed–accuracy tradeoffs and strategic use of a computerized help function. Cluster analysis revealed five distinct groups of participants based on the combination of response accuracy, latency, and help use. Some groups with moderate to high mean WMC acquired the task with predictable performance patterns. Other groups, prevalently under a memory load and with low mean WMC, failed to learn or overused help.     

Assessment of science learning: Living in interesting times

Beginning with a reference to living in a time of both uncertainty and opportunity, this article presents a discussion of key areas where shared understanding is needed if we are to successfully realize the design and use of high quality, valid assessments of science. The key areas discussed are: (1) assessment purpose and use, (2) the nature of assessment and the importance of research on learning, (3) assessment design processes, (4) validity arguments, (5) measurement and statistical inference, (6) affordances of technology, and (7) systems of assessment. After introducing each vital area, the article discusses how each of the five articles in the special issue is connected to the areas. Concluding comments emphasize the reminder that despite the large amount of work to be done, we are well positioned to realize the high quality, valid science education assessments that we need for K‐16 science education. © 2012 Wiley Periodicals, Inc. J Res Sci Teach 49: 831–841, 2012     

Practical Guides

THE ART AND SCIENCE OF RADIO, by Linda Busby and Donald Parker (Boston: Allyn and Bacon, 1984-$20.00).

ELECTRONIC ARTS OF SOUND AND LIGHT, by Ronald Pellegrino (New York: Van Nostrand Reinhold, 1983—$28.50).

TELECONFERENCING HANDBOOK: A GUIDE TO COST-EFFECTIVE COMMUNICATION, by Ellen Lazar et al. (White Plains, New York: Knowledge Industry Publications, 1983—$34.95).

THE CREATIVE CONNECTION: ADVERTISING COPYWRITING AND IDEA VISUALIZATION, by Arthur A. Winters and Shirley F. Milton (New York: Fairchild Publications, 1982—$16.50).

BROADCAST NEWSWRITING AS PROCESS and BROADCAST COPYWRITING AS PROCESS by J. Clark Weaver (New York: Longman, 1984—price not given, paper).

PUBLIC RELATIONS/PUBLICITY: A KEY LINK IN COMMUNICATIONS, by Lois Ehrenkranz and Gilbert Kahn (New York: Fairchild, 1983—$14.50).

EXPERTS IN ACTION: INSIDE PUBLIC RELATIONS, by Bill Cantor (New York: Longman, 1984—$29.95/ 14.95).     

Towards an explanatory and computational theory of scientific discovery

We propose an explanatory and computational theory of transformative discoveries in science. The theory is derived from a recurring theme found in a diverse range of scientific change, scientific discovery, and knowledge diffusion theories in philosophy of science, sociology of science, social network analysis, and information science. The theory extends the concept of structural holes from social networks to a broader range of associative networks found in science studies, especially including networks that reflect underlying intellectual structures such as co-citation networks and collaboration networks. The central premise is that connecting otherwise disparate patches of knowledge is a valuable mechanism of creative thinking in general and transformative scientific discovery in particular. In addition, the premise consistently explains the value of connecting people from different disciplinary specialties. The theory not only explains the nature of transformative discoveries in terms of the brokerage mechanism but also characterizes the subsequent diffusion process as optimal information foraging in a problem space. Complementary to epidemiological models of diffusion, foraging-based conceptualizations offer a unified framework for arriving at insightful discoveries and optimizing subsequent pathways of search in a problem space. Structural and temporal properties of potentially high-impact scientific discoveries are derived from the theory to characterize the emergence and evolution of intellectual networks of a field. Two Nobel Prize winning discoveries, the discovery of Helicobacter pylori and gene targeting techniques, and a discovery in string theory demonstrated such properties. Connections to and differences from existing approaches are discussed. The primary value of the theory is that it provides not only a computational model of intellectual growth, but also concrete and constructive explanations of where one may find insightful inspirations for transformative scientific discoveries.     

Applying machine learning in science assessment: a systematic review

ABSTRACT

Machine learning (ML) is an emergent computerised technology that relies on algorithms built by ‘learning’ from training data rather than ‘instruction’, which holds great potential to revolutionise science assessment. This study systematically reviewed 49 articles regarding ML-based science assessment through a triangle framework with technical, validity, and pedagogical features on three vertices. We found that a majority of the studies focused on the validity vertex, as compared to the other two vertices. The existing studies primarily involve text recognition, classification, and scoring with an emphasis on constructing scientific explanations, with a vast range of human-machine agreement measures. To achieve the agreement measures, most of the studies employed a cross-validation method, rather than self- or split-validation. ML allows complex assessments to be used by teachers without the burden of human scoring, saving both time and cost. Most studies used supervised ML, which relies on extraction of attributes from student work that was first coded by humans to achieve automaticity, rather than semi- or unsupervised ML. We found that 24 studies were explicitly embedded in science learning activities, such as scientific inquiry and argumentation, to provide feedback or learning guidance. This study identifies existing research gaps and suggests that all three vertices of the ML triangle should be addressed in future assessment studies, with an emphasis on the pedagogy and technology features.