Gwen Nugent

Pictures, audio, and print: symbolic representation and effect on learning

Can presentations by an iconic system (pictures) and a linguistic system (print or audio) aid learning? Tests given fourth-to-sixth graders showed that they alternate between systems, using each to assimilate information. However, when content differed between the systems — and this information was presented simultaneously (visual + audio) — processing of the information was not as effective.

Impact of Robotics and Geospatial Technology Interventions on Youth STEM Learning and Attitudes

Abstract This study examined the impact of robotics and geospatial technologies interventions on middle school youth’s learning of and attitudes toward science, technology, engineering, and mathematics (STEM). Two interventions were tested. The first was a 40-hour intensive robotics/GPS/GIS summer camp; the second was a 3-hour event modeled on the camp experiences and intended to provide an introduction to these technologies. Results showed that the longer intervention led to significantly greater learning than a control group not receiving the instruction, whereas the short-term intervention primarily impacted youth attitude and motivation. Although the short-term intervention did not have the learning advantages of a more intensive robotics camp, it can serve a key role in getting youth excited about technology and encouraging them to seek out additional opportunities to explore topics in greater detail, which can result in improved learning.

The use of digital manipulatives in k-12: robotics, GPS/GIS and programming

Faculty from 4-H Youth Development, Biosystems Engineering, and Education have collaborated to develop and implement an innovative robotics and geospatial technologies program, delivered in an informal learning setting of 4-H clubs and afterschool programs. Aimed at middle school youth, the program uses robotics and global positioning system (GPS) receivers and geographic information system (GIS) software to provide hands-on, self-directed learning experiences that promote personalized comprehension of science, technology, engineering, and math (STEM) concepts through experimentation. The goals of the program are to prepare youth for the 21st Century workplace by providing them opportunities to learn STEM concepts and foster positive attitudes about STEM. Funded by the National Science Foundation, the project has undergone extensive research and evaluation over the three years of the project. Results have focused on the projects impact on: a) youth learning of computer programming, mathematics, geospatial concepts, and engineering/robotics concepts and b) youth attitudes and motivation towards science, technology, engineering, and mathematics. In contrast to the preponderance of research on educational robotics relying on anecdotal and descriptive strategies, this research uses empirical, quantitative methods involving the use of comparison groups and pre-post analyses.

A Model of Factors Contributing to STEM Learning and Career Orientation

The purpose of this research was to develop and test a model of factors contributing to science, technology, engineering, and mathematics (STEM) learning and career orientation, examining the complex paths and relationships among social, motivational, and instructional factors underlying these outcomes for middle school youth. Social cognitive career theory provided the foundation for the research because of its emphasis on explaining mechanisms which influence both career orientations and academic performance. Key constructs investigated were youth STEM interest, self-efficacy, and career outcome expectancy (consequences of particular actions). The study also investigated the effects of prior knowledge, use of problem-solving learning strategies, and the support and influence of informal educators, family members, and peers. A structural equation model was developed, and structural equation modeling procedures were used to test proposed relationships between these constructs. Results showed that educators, peers, and family-influenced youth STEM interest, which in turn predicted their STEM self-efficacy and career outcome expectancy. STEM career orientation was fostered by youth-expected outcomes for such careers. Results suggest that students’ pathways to STEM careers and learning can be largely explained by these constructs, and underscore the importance of youth STEM interest.

Design, Development, and Validation of Learning Objects.

A learning object is a small, stand-alone, mediated content resource that can be reused in multiple instructional contexts. In this article, we describe our approach to design, develop, and validate Shareable Content Object Reference Model (SCORM) compliant learning objects for undergraduate computer science education. We discuss the advantages of a learning object approach, including positive student response and achievement, extension to other settings and populations, and benefits to the instructor and developers. Results confirm our belief that the use of modular, Web-based learning objects can be used successfully for independent learning and are a viable option for distance delivery of course components.

An Integrated Framework for Improved Computer Science Education: Strategies, Implementations, and Results

This paper describes the Reinventing Computer Science Curriculum Project at the University of Nebraska-Lincoln. Motivated by rapid and significant changes in the information technology and computing areas, high diversity in student aptitudes, and high dropout rates, the project designed and implemented an integrated instructional/research framework. The framework is based around 10 general design strategies that incorporated administrative, instructional, and research principles. The framework consists of a placement examination, three suites of structured laboratory assignments, multimedia learning objects, and educational evaluation and research designs. The results of implementing the framework in our introductory courses are encouraging and insightful. While validating some of our designs, our research also identified areas for further development and research.

Robots in K-12 Education: A New Technology for Learning

Educational robotics provides students with a learning environment that has the potential to successfully integrate concepts within science, technology, engineering, and mathematics (STEM) into K12 learning environments in class, after school, or for robotics competitions. Robots in K-12 Education: A New Technology for Learning explores the theory and practice of educational robotics in the K-12 formal and informal educational settings, providing empirical research supporting the use of robotics for STEM learning. An essential resource for STEM educators, the book explores processes and strategies for developing and implementing robotics-based programs and documents the impact of educational robotics on youth learning by presenting research-based descriptions of robotics technologies and programs, as well as illustrative examples of learning activities, lessons, and assessments.

Evaluating the use of learning objects in CS1

Learning objects (LOs) have been previously used in computer science education. However, analyses in previous studies have been limited to surveys with limited numbers of LOs and students. The lack of copious quantitative data on how LOs impact student learning makes detailed analysis of LO usefulness problematic. Using an empirical approach, we have studied a suite of LOs, comprehensive in both the content covered and the range of difficulty, deployed to CS1 courses from 2007-2010. We review previous work on predictors of achievement and impact of active learning and feedback. We also provide a high-level overview of our LO deployment. Finally, based on our analysis of student interaction data, we found that (1) students using LOs have significantly higher assessment scores than the control group, (2) several student attributes are significant predictors of learning, (3) active learning has a significant effect on student assessment scores, and (4) feedback does not have a significant effect, but there are variables with significant moderating effects.

Empirical usage metadata in learning objects

The iLOG Project (Intelligent Learning Object Guide) is designed to augment multimedia learning objects with information about (1) how a learning object has been used, (2) how it has impacted instruction and learning, and (3) how it should be used. The goal of the project is to generate metadata tags from data collected while students interact with learning objects; these metadata tags can then be used to help teachers identify learning objects that match the educational and experiential backgrounds of their students. The project involves the development of an agent-based intelligent system for tracking student interaction with learning objects, in tandem with an extensive learning research agenda. This paper provides an overview of this NSF-funded project, focusing on the instructional approach and research on varying levels of active learning and feedback. Using a randomized design and a hierarchical linear modeling framework, research showed that the active learning conditions resulted in significantly higher student learning. The elaborative feedback results approached (p = .056), but did not reach, the established significance criteria of alpha = .05. Both active learning conditions and one of the elaborative feedback conditions resulted in significantly higher content assessment scores compared to a control group.

Revising computer science learning objects from learner interaction data

Learning objects (LO) have previously been used to help deliver introductory computer science (CS) courses to students. Students in such introductory CS courses have diverse backgrounds and characteristics requiring revision to LO content and assessment to promote learning in all students. However, revising LOs in an ad hoc manner could make student learning harder for subsequent deployments. To address this problem, we present a systematic revision process for LOs (LOSRP) using proven techniques from educational research including Blooms Taxonomy levels, item-total correlation, and Cronbachs Alpha. LOSRP uses these validation methods to answer seven questions in order to diagnose what needs to be revised in the LO. Then, LOSRP provides guidelines on revising LOs for each of the seven questions. As an example, we discuss how LOSRP was used to revise the content and assessment for 16 LOs deployed to over 400 students in introductory CS courses in 2009. Lastly, although initially designed for LO revision, we briefly discuss how LOSRP could be used for assessment revision in intelligent tutoring systems.