Measuring Science Interest: Rasch Validation of the Science Interest Survey

Lamb, Richard; Annetta, Leonard A.; Meldrum, Jeannette; Vallett, David

doi:10.1007/s10763-011-9314-z

Cited by 106 publications

(68 citation statements)

References 46 publications

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“…Our results also suggest a possible relationship between affective engagement (showing interest in tasks) and participation by ELLs. Showing interest in academic tasks directs additional attention toward the object or activity (Hidi, ; Krapp, ; Lamb, Annetta, Meldrum, & Vallett, ; Patrick, Mantzicopiulos, & Samarapungavan, ). From this perspective, interest is the antecedent to persistence on cognitive tasks (Decety, Michalska, & Kinzler, ; Scherer, ; Seel & Winn, ).…”

Section: Implications For Teaching and Learningmentioning

confidence: 99%

Engineering Literacy and Engagement in Kindergarten Classrooms

Aguirre-Muñoz¹,

Pantoya²

2016

J of Engineering Edu

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Background Little is understood about how kindergarten students respond to literacy‐enriched engineering activities and how engineering‐centered literature (picture and story books) can be used to support engineering engagement and content understanding. Purpose This study sought to understand the effect of engineering‐centered literature and academic conversations to enhance linguistically diverse kindergarten students' engagement with engineering content. Design/Method A withdrawal single‐case study with multiple measures was conducted to document the effects of the literacy‐enriched engineering intervention program. The frequencies of three types of engagement were recorded: behavioral, affective, and cognitive engagement. Participation in discussions was also recorded to monitor academic conversations. Six female kindergarten students whose first language was not English, representing three ability levels, were targeted for data collection. Results The relative value of the types of engagement and discussion participation increased. These increases generally declined when the intervention was withdrawn. All ability levels showed significant increase during intervention. Engagement peaked during hands‐on engineering design activities for all students. A second peak occurred during the engineering picture book read‐aloud with active engagement activities. Conclusion The combination of activities in the intervention is effective for English language learners and can improve engagement for all ability levels. Academic conversations enhanced all lessons by increasing discussion participation. Results show a functional relationship between enjoying the learning activities and being motivated to participate in discussion. Taken together, engineering‐centered literature and academic conversations are effective tools for broadening meaningful participation in engineering education.

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Section: Implications For Teaching and Learningmentioning

confidence: 99%

Engineering Literacy and Engagement in Kindergarten Classrooms

Aguirre-Muñoz¹,

Pantoya²

2016

J of Engineering Edu

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“…Over the course of 15 hours of play, the subjects generated approximately 450,000 data points for training, analysis, and development of parameters around critical reasoning tasks using IRT and CDA. Upon completion of the presentation of training data to the STAC-M researchers presented the STAC-M with modification of the Piagetian conservations tasks for analysis [17,35].…”

Section: Resultsmentioning

confidence: 99%

“…Composite actions are accounted for in educational and psychological measurement models through the a (task discrimination), b (task difficulty), and c (guessing) parameters under item response theory (IRT). Item response theory is a psychometric theory and paradigm for the design, analysis, and scoring of mental measures of ability, attitudes, and other constructs [17]. Under IRT, composite tasks are assigned probabilities in relation to each of the parameters a, b, and c. The combination of probabilities is combined with second measurement method known as cognitive diagnostics.…”

Section: Intentionmentioning

confidence: 99%

Computational Modeling of Teaching and Learning through Application of Evolutionary Algorithms

Lamb

Premo

2015

Computation

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Within the mind, there are a myriad of ideas that make sense within the bounds of everyday experience, but are not reflective of how the world actually exists; this is particularly true in the domain of science. Classroom learning with teacher explanation are a bridge through which these naive understandings can be brought in line with scientific reality. The purpose of this paper is to examine how the application of a Multiobjective Evolutionary Algorithm (MOEA) can work in concert with an existing computational-model to effectively model critical-thinking in the science classroom. An evolutionary algorithm is an algorithm that iteratively optimizes machine learning based computational models. The research question is, does the application of an evolutionary algorithm provide a means to optimize the Student Task and Cognition Model (STAC-M) and does the optimized model sufficiently represent and predict teaching and learning outcomes in the science classroom? Within this computational study, the authors outline and simulate the effect of teaching on the ability of a "virtual" student to solve a Piagetian task. Using the Student Task and Cognition Model (STAC-M) a computational model of student cognitive processing in science class developed in 2013, the authors complete a computational experiment which examines the role of cognitive retraining on student learning.

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“…To measure whether students experienced a change in attitudes and habits during the quarter the learning community was in place a survey developed by the authors was administered. The survey is based on previous surveys of attitudes toward computer science [4,14,22,23].…”

Section: Discussionmentioning

confidence: 99%

A Computer Science Linked-courses Learning Community

Settle

Lalor

Steinbach

2015

Proceedings of the 2015 ACM Conference on Innovation and Technology in Computer Science Education

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Previous work has shown that factors such as student engagement and involvement can impact progress for computer science majors. One promising approach for improving student engagement is learning communities, which have a long history in academia but are relatively uncommon in computing. In this article we describe a linked-courses learning community for women and men of color majoring in development-focused computing degrees. We provide logistical information about the first offering of the learning community and assess the effectiveness of the community via a student survey. Our results show that students in the learning community are more likely to report that they have support for success in computer science courses and that they are a part of a community of programmers.

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Measuring Science Interest: Rasch Validation of the Science Interest Survey

Cited by 106 publications

References 46 publications

Engineering Literacy and Engagement in Kindergarten Classrooms

Engineering Literacy and Engagement in Kindergarten Classrooms

Computational Modeling of Teaching and Learning through Application of Evolutionary Algorithms

A Computer Science Linked-courses Learning Community

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