GeniGUIDE will investigate how to best support students and teachers as they use Geniverse in the classroom. Powered by an intelligent tutoring system (ITS) developed by partners at NCSU, the GUIDE system will provide real-time feedback on student progress, identify problem areas and give both teachers and students assistance and strategies for success.

The goal of the GeniGUIDE project is to improve student learning of genetics content by developing and researching a layered learner guidance system that aids students and informs student-student and student-teacher interactions. GUIDE will be a hybrid system that partners an intelligent tutoring system (ITS) with the practiced pedagogical expertise of the classroom teacher and existing classroom networks of peer support. Such a system can bring to bear the rich user models of ITS and leverage their aggregated knowledge of the class as a whole. As such, this system—teacher and students plus ITS—can act as a critical new guide for student learning support, expanding opportunities for assisting students effectively when they encounter problems, offering insights related to class-wide activity, strategizing for effective next steps and permitting new exploration into how to enhance and deepen student learning.

We will develop and implement GUIDE within Geniverse, an already proven, NSF-funded digital learning environment built to support high school genetics. Geniverse is a game-like environment intended for use in the classroom; the GUIDE system will interface directly with Geniverse, using and processing student interactions with the software to inform related guiding interactions in the classroom. We will test and develop the GUIDE system iteratively and collaboratively in real classroom instructional contexts. As part of this development, we will research how such a system can provide useful information in the classroom, how the information can improve support of student learning and in what ways understanding of core genetics content and the science practices of planning and conducting investigations, analyzing and interpreting data and engaging in argument from evidence can improve under such a system. Finally, we will disseminate the results to both public and private sector innovators in the educational technology community.

The project will meet its goal by achieving a series of specific objectives. In particular, we will:

Characterize current supports for deeply digital learning. Our studies will characterize how student learning in the Geniverse learning environment is guided and scaffolded through interactions within the current classroom context. Working collaboratively with experienced Geniverse teachers, we will identify the best opportunities for the GUIDE system to inform and guide interactions and develop the initial GUIDE system requirement specifications.

Develop and integrate the GUIDE system. From the initial system specifications, we will use an iterative approach to develop, integrate with Geniverse and test the GUIDE system.

Implement the system in classrooms. We will implement iterative versions of the GUIDE system in classrooms to investigate how successfully the system can model student understanding and strategies, identify how this information can be delivered in a manner that provides actionable guidance and study how the guidance provided affects classroom student–teacher–technology interactions.

Research GUIDE's impact on student learning. We will use student learning outcomes from the Geniverse learning environment and documented use of the GeniGUIDE system in the classroom in order to understand how GUIDE supports student learning of genetics concepts and the practices of planning and conducting investigations, analyzing and interpreting data and engaging in argument from evidence.

Disseminate the project findings. We will disseminate the project findings, guidelines, materials and software through multiple channels: academic papers, articles in publications aimed at teachers, the websites of project partners, social media channels and the newsletter @Concord in print and electronic form. Use of the developed GUIDE software will be available to educators at no cost.

Principal Investigators

Chad Dorsey
Frieda Reichsman
James Lester
Eric N. Wiebe

Project Inquiries

Project Partners


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Interactive models, powered by real genes, enable students to do simulated experiments, generate realistic and meaningful genetic data and win star ratings for efficient experimentation.

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This material is based upon work supported by the National Science Foundation under Grant No. DRL-1503311. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

In order to understand the potential that the GeniGUIDE system can offer in supporting both learners and teachers, the GUIDE project will research three core questions:

  1. How can an ITS-based learner guidance system best expose information about student practices and conceptual understanding? What information about student learning experiences is most useful for guiding learning in deeply digital environments?
    • What data must be captured, processed and presented in order to characterize this learning most effectively for use by students and teachers?
    • How can different levels of information be isolated or aggregated to provide insight into the learning process within a working classroom? What information about individual users is important? What potentially useful information can be gleaned about groups of users or the aggregated state of a whole class?
    • Do student content knowledge and science practices map to different data streams?
  2. How can this information improve support of student learning in the classroom context?
    • In the classroom context, what situations and information are best handled independently through intervention by the system’s ITS layer?
    • How can such a system best provide guidance to help students leverage the experience and understanding of other students in the classroom?
    • How can information be presented during the course of learning to best inform teachers of actionable, high-leverage opportunities for fostering student learning? How can this presentation circumvent concerns about potentially “scripting” student-teacher interactions?
  3. How does the availability and use of this information ultimately improve students’ knowledge and practices?
    • Does student learning of core disciplinary concepts and practices improve when such a system is in place and operating?
    • How do student-student and teacher-student interactions under this type of guidance system relate to student learning?

Research will take place over a four-year period. We will seek to understand the current instructional context and begin exploring how to operationalize trace data harvesting and analysis in Year 1, using established techniques for software requirements gathering and user needs analysis, along with educational design-based research protocols for classroom observation. In Years 2 and 3, we will test and refine the initial design multiple times using established design-based research methods. We will conduct a broader study of the system in diverse classroom settings in Year 4.

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