Abstract
In this chapter, the authors present the design rationale for and empirical results from a predominantly synchronous three-part online model for the professional development of mathematics teachers in rural contexts. They describe how the design of the components are complementary and are intended to support teachers to develop challenging instructional practices, even when the teachers are geographically remote and dispersed. The three parts include an online course, online video coaching, and online demonstration lessons. They describe how they used conjecture mapping to enhance collaboration within the project team and to inform iterations of the model. They then present empirical results related to each of the components of the model and draw conclusions based upon what they have learned.
TopBackground
The goal of our NSF-funded project was to provide rural teachers access to professional learning experiences that would support visions of rigorous instruction articulated in the Common Core State Standards for Mathematics (CCSSM) (Common Core State Standards Initiative [CCSSI], 2010). Research in mathematics education has shown that using rich tasks to elicit and make public student thinking in ways that involve disciplinary rigor helps students to learn with understanding and broadens access to mathematics (Boaler & Staples, 2008; Lampert et al., 2010). Furthermore, we saw the use of rich tasks and practices associated with disciplinary rigor as aligned with the intentions of the CCSSM authors and the local policy makers who adopted the CCSSM or modified versions of the CCSSM.
Comprehensive analyses of professional development programs in the United States have shown that in order for teachers to develop competency in such ambitious instructional practices they need to engage in sustained, intensive professional development situated close to their own practices and curriculum contexts (Clarke, 1994; Garet et al., 2001; Loucks-Horsley, Hewson, Love, & Stiles, 1998). Furthermore, the professional development should focus teacher attention on how student thinking develops in relation to particular content or instructional sequences (Carpenter et al., 2004; Gamoran et al., 2003; Secada & Adajian, 1997). Such professional development requires sustained access to the kinds of resources that are rarely present in rural contexts (Howley et al., 2005).
Teachers in rural areas face constraints in terms of accessing the expertise and resources required for high-quality professional learning experiences, due largely to their lack of proximity to institutions of higher learning and to a lack of a critical mass of colleagues who teach the same content (Howley & Howley, 2005). Online professional development can be available to geographically dispersed participants (Francis & Jacobsen, 2013), alleviating some of the access issues for teachers in rural contexts.
Key Terms in this Chapter
Teaching Labs: Teaching Labs are our modified version of demonstration lessons. In the latest iteration of our model, Teaching Labs are planned by the project team and taught by one of the team members. We video-record the lesson and edit it to smaller snippets, which are then viewed synchronously by the participants. We use protocols to guide reflection of the lesson snippets.
Swivl: An intelligent technological assistant robot that gathers high quality audio and visual data and automatically uploads data to an online storage space for viewing; the technology provides opportunity for video viewing and annotating after collection.
High-Leverage Discourse Practices: Teaching practices designed to facilitate classroom discussions characterized by purposeful questions, eliciting student thinking, building mathematical content connections, and supporting productive struggle.
Demonstration Lessons: Demonstration lessons are publicly taught lessons, such as what is found in lesson study or fishbowl lessons. We use this term to signify generically publicly taught lessons. Our specific model of demonstration lessons is what we term Teaching Labs, defined below.
Online Video Coaching: A responsive model of coaching that utilizes communicative technology and videos, allowing a coach and teacher to engage in collaborative cycles of planning, instruction, and reflection for the purpose of increasing teacher’s pedagogical and content knowledge to improve instruction from a distance.
Mediating Processes: Observable interactions between participants and the learning environment that show how the learning environment facilitates or mediates participants’ interactions, particularly those conjectured as leading to desired outcomes; intended to produce desired outcomes, which are theoretical conjectures.
Cognitively Demanding Tasks: A complex problem, or set of problems, designed to engage students in exploration of a specific mathematical idea. Such problems build on student’s current understanding to promote mathematical reasoning, problem solving, and discourse by students engaged in the task.
Content-Focused Coaching: A responsive model of coaching involving a (content) expert coach collaborating with teachers through cycles of planning, instruction, and reflection for the purpose of increasing teacher’s pedagogical and content knowledge to improve instruction.
Teacher Noticing: The ability to attend to salient aspects within a learning environment, interpret those aspects to make meaning for the purpose of advancing students’ thinking; noticing sometimes involves decisions to respond and can be considered from multiple perspectives, such as how one perceives a situation, who is perceived in a context, and what is perceived or focused on in the environment.
Zoom: An online video conferencing platform that incorporates audio and video feeds of multiple participants; includes features such as commenting, screen sharing, breakout rooms, and audio recording for the purpose of holding meetings from a distance.
Annotations: A specific comment or question written in the Swivl platform in response to a specific time-stamped moment of practice in the video.
Synchronous Learning Environment: A context for learning in which participants join at the same time and take up activities or interactions simultaneously.
Conjecture Maps: A process of specifying theoretically salient aspects of the design of a learning environment to map out how features of the environment are predicted to work together to produce desired outcomes and to unpack the assumptions and theories of the operation.