Toronto, Canada
April 5-9, 2019
Conference Website
The theme of the AERA 2019 conference is “Leveraging Education Research in a ‘Post-Truth’ Era: Multimodal Narratives to Democratize Evidence.” This meeting offers a wide array of sessions that advance knowledge and connect to policy and practice.
Saturday, April 6
Designing Robots for Children: Multisensory Interactions and Multimodal Assessments (Symposium)
10:25 – 11:55 AM, Sheraton Centre Toronto Hotel, Mezzanine Level, Maple East
In this symposium, a panel of researchers with multidisciplinary backgrounds will introduce the AERA community to the fast-growing research on educational robots for children. The panel will present the current status of educational robotic research, relevant theoretical frameworks, and technological advances involved in the design and assessment of child robot interactions.
Speech Recognition and Processing
Cynthia D’Angelo (University of Illinois at Urbana-Champaign), Chad Dorsey
This presentation will include an overview of speech data collection and speech processing procedures and methods, addressing the question, Q5. What technologies are available to design and evaluate CRI? It will discuss advances and issues surrounding automated speech recognition, speaker diarization (trying to distinguish between multiple speakers in one audio stream), and microphone options.
Automated Assessment of Scientific Reasoning: Developments in the Field (Coordinated Session)
12:20 – 1:50 PM, Fairmont Royal York Hotel, Convention Level, Ballroom
This symposium will be an opportunity to hear about four research-based approaches to the computer-based assessment of scientific thinking and the nature and quality of the feedback these approaches provide. Machine learning and AI are set to transform complex tasks in the coming decades and this symposium will present developments in the field of student assessment in science.
Formative Assessment of Scientific Argumentation Practice Enabled by Automated Text Scoring
Margarita Olivera Aguilar (Educational Testing Service), Hee-Sun Lee, Ou Lydia Liu (ETS), Amy Pallant
This symposium will be an opportunity to hear about four research-based approaches to the assessment of scientific thinking and the nature and quality of the feedback these approaches provide. Three of the four approaches draw on machine learning and natural language processing to automate the process of scoring. The fourth examines whether it is possible to assess higher order reasoning using forced choice and selected responses. Three of the four approaches are working with Grade 6-12 and one with undergraduates. The symposium provides an opportunity to learn about both the success and challenges of these different approaches and to contrast the strengths and weaknesses of each.
Sunday, April 7
Learning Experiences: In Inquiry and Perceptions (Paper Session)
Danielle Cadieux Boulden (North Carolina State University), Eric N. Wiebe (North Carolina State University), Osman Aksit (North Carolina State University), Karen Mutch-Jones (TERC), Santiago Gasca (TERC), Chad Dorsey, Frieda Reichsman, James Lester (North Carolina State University), Trudi Lord
11:50 AM – 1:20 PM, Metro Toronto Convention Centre, 700 Level, Room 715B
Instructional Orchestration With Digital Games: Influences on Students’ Learning Experiences
Digital game-based learning offers potential for students to learn scientific concepts in engaging and authentic environments. Critical to leveraging the affordances of these games to create immersive student learning experiences are teachers and the instructional decision-making that they make during implementation. Using an orchestration framework, this study investigated the instructional decisions made by nine high school biology teachers as they implemented a digital game-based learning tool designed to support student learning of genetics. The authors then present two contrasting cases of teacher implementation to characterize how instructional decision-making with the tool either maximized or minimized the potential of the software to support student learning experiences with epistemic-oriented scientific inquiry.
Overcoming Challenges in Developing and Implementing Next Generation Science Standards–Aligned Instructional Materials and Assessments (Symposium)
11:50 AM – 1:20 PM, Metro Toronto Convention Centre, 700 Level, Room 709
The Next Generation Science Standards (NGSS) offer a vision of three-dimensional science instruction that gives students an active role in learning through the integration of science and engineering practices, crosscutting concepts, and disciplinary core ideas. Since the publication of NGSS, a number of research and development projects have sought to create innovative instructional materials and assessments that align with these three dimensions. As these projects reach maturity, the current session aims to generate productive conversations about overcoming the challenges that arise as the standards are refined and adapted to classroom practice. In a panel discussion format, six teams of researchers, with established projects in NGSS-aligned instruction and assessment, will share solutions and insights.
Designing and Implementing Instructionally Supportive Assessment Tasks for Promoting Three-Dimensional Learning: Challenges Faced and Lessons Learned
Christopher Harris (WestEd), James Pellegrino (University of Illinois at Chicago), Joseph Krajcik (Michigan State University), Dan Damelin, Nonye Alozie (SRI International), Kevin McElhaney (SRI International), Brian Douglas Gane (University of Illinois at Chicago), Diksha Gaur (University of Illinois at Chicago), Mon-Lin (Monica) Ko (University of Illinois at Chicago), Krystal Nacole Alberta Madden (University of Illinois at Chicago), Sania Zahra Zaida (University of Illinois at Chicago), Phyllis Haugabroo Pennock (Michigan State University), Samuel Severance (Michigan State University)
We describe our multi-institutional effort to design and implement instructionally supportive assessment tasks that integrate disciplinary core ideas, science and engineering practices, and crosscutting concepts as called for in the Next Generation Science Standards (NGSS Lead States, 2013). We present our design approach along with example tasks and rubrics, discuss results from implementation, and share challenges encountered and lessons learned from developing the tasks and using them in middle school classrooms.
MTCC Poster Session
3:40 – 5:10 PM, Metro Toronto Convention Centre, 300 Level, Hall C
Precipitating Change: Embedding Computational Thinking Into the Middle School Science Classroom
Nanette Marcum-Dietrich (Millersville University of Pennsylvania), Carolyn Staudt, Rachel Becker-Klein (Peer Associates)
All students need to understand the role of computation and computational thinking within disciplinary problem solving. Opportunities to learn and apply computational thinking are absent from most students’ experiences. Yet there is no need for these opportunities to be inaccessible. With proper tools and approaches, compelling student experiences within science class can be imbued with fundamental computational thinking skills. This project designed, developed and enacted an innovative, technology-rich curriculum for middle school students that addresses critical NGSS-related science standards, engages students in an intriguing, ongoing inquiry-related investigation, and supports the development of key computational thinking (CT) practices. This study suggests that with purposeful integration of the curricular design elements embedding computational thinking practices into the science classroom is possible.
Monday, April 8
Measuring the Impact of Emotions in Informal Learning Environments ( Structured Poster Session)
10:25 – 11:55 PM, Metro Toronto Convention Centre, 800 Level, Room 801A
This session presents 11 empirical investigations that measure emotion in informal environments. Vygotsky considered emotion as the basis of cognition and thought. Positive emotions have also been shown to enhance achievement by encouraging cognitive engagement and motivation. In science museums, it has been linked to greater long-term learning and in art museums it is often the focus of an educational program. However, measuring emotion can be difficult. In informal environments, this is exacerbated by the general lack of control over the environment and the fact that such settings are often designed to manipulate emotions at a large scale. Outcomes of the session will address the validity of different ways to measure emotions in informal settings.
Taxonomy of Student Uncertainty in Scientific Argumentation
Incorporating uncertainty as part of scientific argumentation means acknowledging that there may be incomplete or potentially limited information from which scientists draw conclusions. In the geosciences, scientists routinely must make inferences about the Earth based on observations of the present and testing those observations against hypotheses about Earth history and processes that are not observable. This paper describes how secondary school students incorporate uncertainty while formulating evidence-based scientific arguments.
Understanding Patterns, Visuals, and Changes (Paper Session)
2:15 – 3:45 PM, Metro Toronto Convention Centre, 800 Level, Room 802A
Understanding Visual Artifacts Using Image Analytics in Students’ Scientific Argumentation
Bo Pei, Wanli Xing (Texas Tech University), Hee-Sun Lee
As a way of providing information can be perceived through human senses, images contain more information that cannot be described accurately by text. However, compared with that of texts the scientific evidences of images showed in scientific argumentation is still unclear. Therefore, in this paper, image processing algorithms were implemented to precisely quantify the features of images. Then, Chi-square tests and ANOVA were employed to analyze the relationships between the features and the argumentations made by students in a groundwater simulation platform. The results indicated that the presence of water had a statistically significant effect on the students’ claim and explanation scores. They also provide some implications about usage of machine learning and image processing technologies in science education.