Is there any research to back up these ideas?

Learnics is committed to ensuring that teachers find learning behavior data to be both meaningful and actionable. To achieve this mission, Learnics partners with researchers to gain a deeper understanding of the way students learn online and develops analytics and training modules to help teachers gain insight and take steps to improve digital learning both inside of their classroom and out.

Research is a critical component of successful and innovative instructional tools and strategies. Our team has conducted extensive research in order to provide the more effective and efficient resources in learning analytics. 

Below are a few examples:

An Action Research Study of Teachers' Use of Learning Analytics as a Formative Practice

Author: Isabel Resende

Dissertation Chair: Dr. Douglas Lare

Dissertation Committee Members: Dr. Greg Cottrell, Dr. Jason Engerman & Dr. Richard Otto

Dissertation Abstract:

Access to technology in schools has increased dramatically over the past several years, and in turn teachers have had to think differently about their instructional practice. With ubiquitous computing, students access information, create information, share information, and communicate with peers without the confines of time and space (Glazatov, 2012). Teachers are faced with the challenge of identifying instructional practices that integrate technology into the learning process, but more importantly they are faced with the challenge of understanding and evaluating how technology as an instructional resource interacts with other aspects of the instructional design process (Glazatov 2012).

Learning analytics is “...the use of analytics techniques to help target instructional, curricular, and support resources to support the achievement of specific learning goals” (Radu, I.r., 2017, p. 509). Analytics has been successfully used in other settings outside of education to support operational decision making. Ultimately, the goal of analytics is to provide the user with information and data to make informed decisions to improve performance (Radu, I.r., 2017). The availability of learning analytics in education presents a unique opportunity for teachers to evaluate how technology as an instructional resource interacts with other aspects of the instructional design to impact student learning. The purpose of this participatory action research study, in a middle school setting, was to describe the relationship between the availability of learning analytics and teachers’ instructional practice. The study was based on the following research questions:

• What influence does the availability of learning analytics have on teacher instructional practice?
• Do instructional practices change on an individual student level based on the results of the learning analytics
• Will teachers use learning analytics as part of their formative practices to adjust student learning?
• What factors contribute to the use of the learning analytics and what factors hinder the use of the learning analytics?

The key findings of the study showed when teachers and software application developers collaborate in the development of a tool that meets the needs of classroom teachers, the data collected becomes valuable for the instructional design process. The availability of learning analytics did influence teacher instructional practice. Learning analytics were useful metrics in providing feedback that was used to intervene in student learning. However, the availability of learning analytics did not change the teacher instructional planning for individual students.

Thinking Outside the Box: A Descriptive Study Focusing on the Application of Learning Analytics on Instructional Design

Author: Gregory James Cottrell

Dissertation Chair: Dr. Douglas Lare

Dissertation Committee Members: Dr. Beth Sockman & Dr. Andrew Whitehead

Dissertation Abstract:

The information age has revolutionized how people communicate, access information and learn.  Today’s students are locating, evaluating and using information in significantly different ways than they did just a generation ago (Holman, 2009).    As students evolve their learning strategies, there is a need for teachers to evolve the way in which they instruct.  In a 1:1 school where every student has a personal mobile computer, the digital learning revolution is happening at an accelerated pace.  The aim of this qualitative research was to gain an understanding of how data about student internet activity can influence the instructional design choices that teachers make in order to meet the needs of digital learners.

This dissertation describes how ubiquitous computing has changed the teaching and learning process.  The Technology, Pedagogical and Content Knowledge framework is presented as a lens to understand the complex knowledge systems that teachers use to make instructional decisions.  Finally, the concept of learning analytics is presented and gaps within instructional design as they relate to learning analytics are analyzed.  This dissertation is based on the guiding hypothesis that 1:1 teachers need access to student internet logs in order to make fully informed instructional design decisions.  As stated by Scheffel, Drachsler, Stoyanov & Specht (2014), “in order to support students within a course, teachers should be aware of what the students are doing, how they are interacting with course material and where comprehension problems arise” (p. 117).

In order to gain an understanding of the impact of learning analytics on instructional design, five teachers at a public high school in New Jersey participated in a seven week long research project.  During this project the researcher compiled and provided each teacher with a report of the online behaviors conducted by their students in order to complete an assignment.  Teachers were interviewed prior to receiving the report and again after receiving the learning analytics report.  Teachers also participated in professional learning community meetings with the other participating teachers in order to discuss and reflect upon the impact of an increased awareness of students’ online behaviors.

The findings of this practical action research support the hypothesis that teachers need access to information about student online behaviors in order to make fully informed instructional design decisions.   The findings of this research showed several areas of consensus amongst how teachers incorporated Chromebooks into their pedagogy.  The research also showed that an increased knowledge of student online behaviors did not alter the teachers’ perceived value of technology.  The most significant finding of this research was the identification of several ways that teachers’ instructional design decisions were altered as a result of their increased awareness of online activity.  This finding supports the guiding hypothesis that there are educational benefits associated with providing teachers access to comprehensive learning analytics reports associated with their students.

Student Reflections: Media Literacy & Learning Analytics

Author: Katie S. Quartuch

Dissertation Chair: Dr. Douglas Lare

Dissertation Committee Members: Dr. Andra McClanahan &  Dr. Robert McKenzie

Dissertation Abstract: 

Students’ consumption of media is considerable. Research by Rideout, Roberts, & Foehr (2010), found that young people today are exposed to media for over twelve hours a day, but their ability to think critically about information online and use that information in constructive ways is not evident (Sternglasss, 1997; Hobbs, 2010; Scheibe & Rogow 2012). There is growing alarm about students’ ability to analyze online content, and this has lead to a calling for students to develop the media literacy skills necessary for finding, validating, compiling, and using online content (Barthel, Mitchell, & Hocomb, 2016).

In order for teachers to address the media literacy needs of this students, they must first have a window into how their students are learning online. Learning analytics is a growing field that can be used to help teachers see and understand their students’ online behaviors in order to address their potential skill deficiencies (US Department of Education, 2012). Learning analytics allows educators to track indicators of learning such as a students’ online research, their online source selection, their engagement in online lectures or dialogues, and their collaboration on online projects (Johnson, Adams, Cummins, Estrada, Freeman, and Hall, 2016).

This multiple case study utilized a learning analytics tool called the ThinkingApp to peer behind the curtain at students’ online behaviors. The ThinkingApp is a Google extension created in collaboration with educators in order to collect, organize, and analyze students’ online behaviors. The ThinkingApp was used to collect the online behaviors of six students and to allow the researcher to design interview questions that explored students’ perception of online privacy, how students used their school-issued devices, and what media literacy competencies they utilized. This study found that students were not concerned with their online academic behaviors being collected and were willing to candidly discuss their online behaviors. Additionally, this study found that students were not often asked to perform tasks that required media literacy skills. Finally, this study found that students approached their online work in unique ways, but that they all struggled to recognize the relationship between their attitudes towards school and their online behaviors during school.