More Like this

1. Measuring More to Learn More From the Block Design Test: A Literature Review

   Dunn, Avery C ; Qiao, Alice ; Johnson, Maya R ; Kunda, Maithilee ( January 2021 , Proceedings of the Annual Conference of the Cognitive Science Society)

   null (Ed.)

   The block design test (BDT), in which a person has to recreate a visual design using colored blocks, is notable among cognitive assessments because it makes so much of a person's problem-solving strategy ``visible'' through their ongoing manual actions. While, for decades, numerous pockets of research on the BDT have identified certain behavioral variables as being important for certain cognitive or neurological hypotheses, there is no unifying framework for bringing together this spread of variables and hypotheses. In this paper, we identify 25 independent and dependent variables that have been examined as part of published BDT studies across many areas of cognitive science and present a sample of the research on each one. We also suggest variables of interest for future BDT research, especially as made possible with the advent of advanced recording technologies like wearable eye trackers. 

   more » « less
2. Dynamic impairment classification through arrayed comparisons

   https://doi.org/10.1002/sim.9601  

   Wang, Zheng ; Wang, Zi ; Lyu, Lingyun ; Cheng, Yu ; Seaberg, Eric C. ; Molsberry, Samantha A. ; Ragin, Ann ; Becker, James T. ( January 2023 , Statistics in Medicine)

   The multivariate normative comparison (MNC) method has been used for identifying cognitive impairment. When participants' cognitive brain domains are evaluated regularly, the longitudinal MNC (LMNC) has been introduced to correct for the intercorrelation among repeated assessments of multiple cognitive domains in the same participant. However, it may not be practical to wait until the end of study for diagnosis. For example, in participants of the Multicenter AIDS Cohort Study (MACS), cognitive functioning has been evaluated repeatedly for more than 35 years. Therefore, it is optimal to identify cognitive impairment at each assessment, while the family‐wise error rate (FWER) is controlled with unknown number of assessments in future. In this work, we propose to use the difference of consecutive LMNC test statistics to construct independent tests. Frequency modeling can help predict how many assessments each participant will have, so Bonferroni‐type correction can be easily adapted. A chi‐squared test is used under the assumption of multivariate normality, and permutation test is proposed where this assumption is violated. We showed through simulation and the MACS data that our method controlled FWER below a predetermined level.

    

   more » « less
3. Productive Thinking and Science Learning in Design Teams

   https://doi.org/10.1007/s10763-020-10057-x  

   Guzey, S. Selcen ; Jung, Ji Yoon ( February 2020 , International Journal of Science and Mathematics Education)

   Recent reforms in science education have supported the inclusion of engineering in K- 12 curricula. To this end, many science classrooms have incorporated engineering units that include design tasks. Design is an integral part of engineering and helps students think in creative and interdisciplinary ways. In this study, we examined middle-school students’ naturally occurring design conversations in small design teams and their learning of science as a result of engaging in an engineering and science unit. We found that the proportion of different thought processes used by boys and girls was quite similar. Both girls and boys produced a higher percentage of ideas or thoughts associated with divergent thinking, but a lower proportion in convergent thinking, evaluative thinking, and cognitive memory. In addition, gender composition of design teams influenced thought processes expressed by girls and boys. Interestingly, in mixed teams, both girls and boys expressed less divergent thinking than those in single-sex teams. With regard to science content learning, both girls and boys showed statistically significant learning gains. There were no significant gender differences in the pre- and post-test scores. These results suggest that participating in an engineering design task in small design teams provided students opportunities to engage in productive thinking and enhance their learning of the targeted science concept—ecosystems. 

   more » « less
4. Relational thinking: An overlooked component of executive functioning

   https://doi.org/10.1111/desc.13320  

   Starr, Ariel ; Leib, Elena R. ; Younger, Jessica W. ; Project iLead Consortium ; Uncapher, Melina R. ; Bunge, Silvia A. ( September 2022 , Developmental Science)

   Relational thinking, the ability to represent abstract, generalizable relations, is a core component of reasoning and human cognition. Relational thinking contributes to fluid reasoning and academic achievement, particularly in the domain of math. However, due to the complex nature of many fluid reasoning tasks, it has been difficult to determine the degree to which relational thinking has a separable role from the cognitive processes collectively known as executive functions (EFs). Here, we used a simplified reasoning task to better understand how relational thinking contributes to math achievement in a large, diverse sample of elementary and middle school students (N= 942). Students also performed a set of ten adaptive EF assessments, as well as tests of math fluency and fraction magnitude comparison. We found that relational thinking was significantly correlated with each of the three EF composite scores previously derived from this dataset, albeit no more strongly than they were with each other. Further, relational thinking predicted unique variance in students’ math fluency and fraction magnitude comparison scores over and above the three EF composites. Thus, we propose that relational thinking be considered an EF in its own right as one of the core, mid‐level cognitive abilities that supports cognition and goal‐directed behavior.

   Relational thinking, the process of identifying and integrating relations, develops over childhood and is central to reasoning.

   We collected data from nearly 1000 elementary and middle schoolers on a test of relational thinking, ten standard executive function tasks, and two math tests.

   Relational thinking predicts unique variance in math achievement not accounted for by canonical EFs throughout middle childhood.

   We propose that relational thinking should be conceptualized as a core executive function that supports cognitive development and learning.

    

   more » « less
5. A Framework to Study Human-AI Collaborative Design Space Exploration

   https://doi.org/10.1115/DETC2021-67619  

   Viros-i-Martin, Antoni ; Selva, Daniel ( August 2021 , Proceedings of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference.)

   This paper presents a framework to describe and explain human-machine collaborative design focusing on Design Space Exploration (DSE), which is a popular method used in the early design of complex systems with roots in the well-known design as exploration paradigm. The human designer and a cognitive design assistant are both modeled as intelligent agents, with an internal state (e.g., motivation, cognitive workload), a knowledge state (separated in domain, design process, and problem specific knowledge), an estimated state of the world (i.e., status of the design task) and of the other agent, a hierarchy of goals (short-term and long-term, design and learning goals) and a set of long-term attributes (e.g., Kirton’s Adaption-Innovation inventory style, risk aversion). The framework emphasizes the relation between design goals and learning goals in DSE, as previously highlighted in the literature (e.g., Concept-Knowledge theory, LinD model) and builds upon the theory of common ground from human-computer interaction (e.g., shared goals, plans, attention) as a building block to develop successful assistants and interactions. Recent studies in human-AI collaborative DSE are reviewed from the lens of the proposed framework, and some new research questions are identified. This framework can help advance the theory of human-AI collaborative design by helping design researchers build promising hypotheses, and design studies to test these hypotheses that consider most relevant factors.

    

   more » « less