Chapter 1 Introduction to the Sci-I Project

The Science Investigations (Sci-I) Project was designed to provide students in grades 6-9th a supported experience in developing and answering testable scientific questions from real-world data. This project was a collaborative initiative between scientists, educators, and students that focused on the process of developing questioning techniques and using data. We focused on students using online professionally-collected data (e.g., data collected by a scientist as part of a larger research project/program) to address the students’ question(s). However, the same process can be applied to using student-collected (or learner-generated) data, data collected by the student in a field or laboratory experience, just as easily.

The short-term goals of the Sci-I Project were to increase educators’ and students’:

understanding of the process of science,
use of real-world data, and
confidence in designing, conducting, and presenting scientific investigations.

Our overarching long-term goal was to help participating students’ engage in science and build their identity as a scientist through awareness of what it means to be a scientist.

Through this year-long program, participating students learned how to:

write a testable question (and corresponding hypothesis) that are grounded in data,
respond to a Request for Proposals (RFP),
accept constructive, critical review and modify/iterate their question(s) and/or investigation design,
conduct a scientific analysis of data,
develop figures to best represent data,
develop a scientific conference poster (or other ways to communicate their scientific results), and
present work at a Student Research Symposium.

This collaborative program between scientists and K-12 schools was designed to represent the realistic and often nonlinear practices involved in scientific research authentically. For the 2015-18 academic years we utilized online datasets from the Palmer Station Long-Term Ecological Research (LTER) and other online, professionally-collected polar datasets to explore the development of this teaching model, driven largely by our funding source and professional connections with the Palmer LTER project.

This document highlights the various components of the Sci-I Project with links to resources, activities, templates, and examples from our implementation in 2015-18. The final section of this document highlights some of the key evaluation findings and lessons learned from the project with regards to the impact on teaching and learning the process of science and use of real-world data.

1.1 What was the focus of the Sci-I Project?

Scientists use a range of investigation types that fall primarily into three categories: Experimental, Observational, and Descriptive. Experimental Investigations are used to assess causal relationships between variables by changing something within the system (treatment group) and comparing the subsequent results with an unchanged system (control group). Observational Investigations seek to draw conclusions of relationships by observing a system without changing something within the system (aka there are not control or treatment groups). Both of these kinds of investigations have clearly defined independent and dependent variables as you are investigating a relationship among different variables. Finally, in Descriptive Investigations researchers attempt to draw conclusions about the system based on what is going on in the system. The emphasis is on describing what is happening overall, and thus again there are no control or treatment groups and sometimes no clear dependent variables.

In the Sci-I Project, students were encouraged to generate questions through Descriptive Investigations, instead of following a guided set of questions from a textbook or lesson plan more common in Experimental Investigations. Both educators, and their students were supported through a process of researching science topics and investigating answers to developing their own testable questions from an existing dataset. These Descriptive Investigations were designed to help students:

describe what they see in the data as it relates to a real-world phenomenon or process,
build broader confidence in doing science and addressing uncertainty in their analysis, and
utilize and take advantage of expanded access to professionally collected online data.

Through the project we empahsized more explicitly teaching students how to distinguish between questions that could only be answered with scientific data (aka testable questions), and those that we could “look up” online or in print (aka “googlable questions”). Students were provided the time and support to build their knowledge base on a topic area in order to generate their scientific curiosity about a topic.

Another key set of skills the students developed through the project was how to collect, process, and visualize data to answer their questions. Students learned to discern which data they would need to answer their questions; how to process the data to limit and/or summarize their data to answer their questions; and finally, how to visualize the data to explore and draw conclusions.

A unique aspect of the project was that neither the students nor the educators knew the answer to the students’ testable questions at the start of the project (as opposed to most in-class investigations that have a “right” answer the teacher is trying to help the students discover). For the Sci-I Project, it was completely up to the students to determine a way to make sense of their data and communicate their results to their peers, educators, and scientists.

1.2 How did the Sci-I Project work?

The Sci-I Project was a year-long initiative consisting of several distinct phases - a professional development workshop for educators, school implementation, and a student research symposium.

1.3 Collaboration with Educators

Each year-long implementation began with a week-long summer professional development workshop focused on allowing educators to dive deeply into the process of science as learners and educators. A primary focus was on providing the educators the opportunity to participate in a condensed version of the process their students would be doing with data and reflected upon their own learning. Additionally, they interacted with a range of scientists to learn how each scientist conducts their work and what their research findings demonstrate. The secondary emphasis of the workshop was to enable educators to explore bringing the authentic process of science and use of real-world data into their teaching. They reflected on how to scaffold and support the various skills with their students by using samples of students work to brainstorm approaches with one another. Finally, the workshop fostered a community of like-minded, data-interested educators that were learning from one another. Further details regarding the workshop can be found in the “Summer Educator Workshop” section.

1.4 School Implementation

The school-year implementation within the classrooms contained three stages:

generating investigation interests,
conducting investigations, and
communicating findings.

The first stage began with identifying student groupings and providing opportunities for the students to explore real-world data and brainstorm ideas for their investigations. Students then developed their questions and fleshed out their ideas in their Investigation Mini-Proposals (modeled off of a National Science Foundation Request for Proposals). The Sci-I Project team provided activities, templates, and a synchronous webinar to help support the educators during this stage (examples and further details can be found in the “In-Year Educator Support” section).

The next stage of the project consisted of students committing to their ideas and conducting their investigations. Students submited their Investigation Mini-Proposals and received feedback from scientists and the Sci-I Project team. Using these reviews, the students adapted their approach and conducted their investigations. Once complete, the students developed a communication platform (most created scientific conference posters) to share their investigation results within their school. Similar to the first stage, the Sci-I Project team provided activities, templates, and a synchronous webinar to help support the educators and students during this phase (further details regarding this stage can be found in the “Mini-Proposals” section).

The final stage of the project – Student Research Symposium – brought the educators, students, scientists, and the Sci-I Project staff together to celebrate the accomplishments of the year. Due to space constraints of the hosting venue and resource constraints within schools it was rarely possible for every participating student to attend the symposium. Therefore, each educator determined which groups of students attended the Sci-I Project Student Research Symposium in the Spring, usually hosted at a local University (though the hosting venue can easily be changed to whatever is most convient for the organizers and participating educators). The event consisted of two main features: poster session and scientist panel. Through the scientific Poster Session, students presented their work to invited scientists as well as the other students and educators from other local participating schools. The Scientist Panel, consisting of emerging and advanced career scientists, was an opportunity for students to lead the conversation on topics of interest and ask participating scientists about their careers. Further details regarding this culminating event can be found in the “Student Research Symposium” section.

1.5 Budget & Timeline

The resources necessary to conduct the Sci-I Project included staff time, participant support, and materials to run the in-person events. The Sci-I Project team worked part-time (on average 20% per week) throughout the year to manage the project. The timing per week varied based on the task and timeline (Table 1).

Table 1.1: Description of the various tasks to accomplish to run the project and the general timeline to accomplish each task.
Task	Timeline
Determine summer workshop dates	December (2 hours)
Prepare and send program announcement	January (6 hours)
Review applications, select participants	March (20 hours)
Line up summer workshop logistics (food, room, speakers, etc.)	1-2 months before workshop (20 hours)
Conduct and follow-up summer workshop	June/July (80 hours)
Determine date for Student Research Symposium (SRS) and date for submitting mini-proposals	At workshop - NA
Coordinate submission of mini-proposals	3 months before SRS (2 hours)
Provide feedback on mini-proposals	3 weeks post submission (20 hours)
Line up SRS logistics (food, room, speakers etc.)	1-2 months before SRS (10 hours)
Coordinate with teachers for student projects	3 weeks prior to SRS (10 hours)
Conduct and follow up SRS event	At SRS (20 hours)

The primary budgetary requirements for the project involved:

Summer Professional Development Workshop: costs pertained to room rentals, meals, accommodations, materials, and travel (roughly $20,000-35,000 for approximately 25 educators for 4 days of residential training)
Educator Stipends: we split the stipend in two components, one following the workshop and one following the Student Research Symposium ($500 / educator total; 25 educations = $12,500)
Student Research Symposium: costs pertained to room rentals, coffee, and lunch for participating scientists, and materials (~$3,500-5,000)

1.6 What were benefits of the Sci-I Project approach?

Providing this year-long project, with support for educators and scaffolding for students, had multiple benefits for changing the way the process of science was taught and how real-world data were used in classrooms across the country. Some of the benefits of participating in the Sci-I Project, as reported by educators, included:

Accessing available online datasets with support for how to use the data,
Participating in a project with real scientists that highlighted the students work as scientists and the collaborative nature of science,
Increasing student engagement in the project, in science overall, and with the host universities,
Being part of something larger than just their classroom or school, and
Providing a context and relevance to the work for the students beyond a classroom assignment.

The Sci-I Project made science come to life for the participating students in a different way than typical classroom instruction. Through the project we leveraged current research regarding how to integrate data into science instruction, teaching the process of science, and engaging students in STEM. The students conducted science in the same manner that professional scientists do every day. They received feedback from one another and scientists after developing an idea and after analyzing their results. This empowered the students to take ownership of their investigation and results, which in turn increased their engagement in science (as supported by other findings from Marcus et al. 2010, Aschbacher et al. 2013, Christensen et al. 2015).

Beyond the students, the Sci-I Project supported the classroom teachers in facilitating this transformative experience for their students by building their own confidence in conducting the process of science in authentic ways (as suggested by Duschl & Grandy 2012). This increased personal confidence enabled the educators to feel comfortable altering their approach to teaching and integrating the process of science into their curriculum (Barrow 2006, Hollingshead 2009, Khoboli & O’Toole 2012). Additionally, a key aspect of the project was that the Sci-I Project staff demonstrated how science is collaborative and full of different depths and breadth of feedback. Educators reported that benefits of the feedback component of the project were that the participating educators were exposed to different kinds of feedback for their students and that the students took the feedback seriously as it was coming from “a scientist” (rather than just their teacher).

Benefits to the students in working with the real-world data in an authentic manner included unpacking the process of how to work with data, expanding their data literacy skills, and helping them develop an understanding of how to ask and answer questions from data. Through these increased skills students gained an identity as a researcher and started seeing themselves as researchers (similar to other project liks Marcus et al. 2010 and NRC 2012). The walls of “scientists versus students” started to break down, and students thought of themselves as scientists who could make sense of the information with which they were given.

Finally, focusing on first building the educators’ confidence and comfort in using real world data meant that the educators also gained the skills themselves to transfer into different situations. For example, the data literacy skills practiced through the Sci-I Project could be incorporated into the educators’ analyses of student-data for data-based instruction (Mandinach & Gummer 2016), and in their integration of data into their subject area teaching (Partners in Data Literacy 2019, Kastens & Krumhansl 2015). Additionally, seeing the accomplishments and empowerment of the students through this project, educators were able to rethink how they integrate student-led inquiry into their curriculum (as suggested by Keys & Bryan 2001, Barrow 2006).

1.7 How did the Sci-I Project develop?

We developed this Sci-I Project approach based on current research in educator professional development and on opportunities to successfully increase student engagement in and identification with science (Barrow 2006, Hollingshead 2009, Khoboli & O’Toole 2012). Additionally, the approach was built on the foundation of previous programming focused on connecting educators, students, and scientists and promoting the process of science and use of real-world data (Hunter-Thomson et al. in review).

We will describe the evolution of the approach through these projects here. For multiple years we coordinated a science-based 3-hour event for local schools to come to Rutgers University to engage with scientists. To develop the program beyond just students coming to campus for a day, we expanded the program in 2010 to include a student poster session based on projects the students did at their schools prior to attending ( Rutgers Ocean Day). The desire was to support students in asking their own science-related questions. However, often times we heard from participating educators that the students, and teachers, did not know where to start in asking open-ended science investigations rather than conducting science projects about known information. Additionally, many scientists reviewing their projects at the in-person event wished they could have provided feedback to the students earlier on in the process of their projects to help redirect them earlier in more productive directions. We saw a need for more support for students, teachers, and scientists to facilitate authentic experiences with science together.

In 2012 the National Science Foundation Polar Division funded Dr.s Grace Saba and Brad Seibel to conduct research on the physiological impacts of ocean acidification on Antarctic krill. As part of this research project, we developed a year-long educational outreach program (2013-14) to connect students from 15 high schools in Kansas (Saba and Seibel’s home state) with the research mission and process of science. As part of the outreach efforts, Project Planting AntaRctica in KAnsas (PARKA), students were asked to develop their own investigation to present at a culminating Student Research Symposium. Based on the participating teachers requests, we added a proposal review component so the students would receive feedback on their ideas prior to completing the projects. Not surprisingly, most students conducted Experimental or Observational Investigations. Additionally, the questions the students asked, the data they used, and their analysis skills varied across the projects. We wondered if there was more that we could provide the students and teachers to help working with real-world data.

The following year we built from lessons learned in the Project PARKA in another National Science Foundation Polar Division supported broader impact project, Project CONVERGE, with Dr.s Josh Kohut, Matt Oliver, Kim Bernard, Peter Winsor, and Bill Fraser. This research project focused on exploring the connections between physical oceanography and various aspects of the food web to explain foraging behaviors of one of the main predators, Adelie penguins. During the 2014-15 academic year, 22 middle and high school classrooms from New Jersey and New York participated in the research mission, via a professional blog, and conducted their own ocean-related investigations. The students had access to the scientists data through an online portal, as well as a primer to understand the different datasets which was written for a middle school reading level. Almost half of the students conducted Descriptive Investigations using the data from the research mission, while the other half did Experimental or Observational Investigations relating to other topic areas. The questions the students asked, the data they used, and their analysis skills still varied across the projects, but not as much as before. Participating teachers and students reported greatly enjoying and appreciating the experience and opportunity to work with real-world data (Kohut et al. 2017).

Therefore, starting in fall 2015 we developed the idea and approach for the Sci-I Project to focus attention on bringing the process of science, real world data, and Descriptive Investigations more to the forefront for middle and high schools across the country. From 2015-18 our work was funded by the National Science Foundation Polar Division (Grant #PLR-1525635) and thus we had a specific emphasis on the students using professionally collected data from the polar regions. However, the approach is transferable to Descriptive Investigations using any kind of discipline-specific dataset. With a focus on the process of science and use of real-world data, separate from content, we have seen a remarkable increase in the consistency and quality of the questions the students asked, the data they used, and their analysis skills.