An E-Learning Approach to Data Information Literacy Education

This paper presents the University of Minnesota Libraries’ contributions to the ongoing Data Information Literacy project, an IMLS-funded project to educate the next generation of escientists through developing a library-run curriculum. Our project team at the University of Minnesota interviewed graduate students in Civil Engineering to determine their needs in data management and curation. We found many skill areas that were missing or needed support in the graduate program and proposed a list of learning outcomes that might be addressed through library training efforts. This paper will focus on our resulting approach to providing Data Information Literacy (DIL) instruction utilizing Google tools (Sites, Drive, YouTube) to present a self-paced, interactive online course. The paper also provides an examination of our assessment methodology and discusses our findings after a pilot launch with Civil Engineering graduate students in Fall 2012. Introduction Since the announcement from the National Science Foundation that all grant funding proposals submitted after January 2011 must include a data management plan (DMP), academic libraries have experimented with ways of providing support and education for researchers at their institutions. At the University of Minnesota, we saw strong demand for guidance on writing and complying with this requirement. This high level of interest required a cross-disciplinary approach to teaching data management skills 1 . Although successful, this instructional approach did not facilitate in-depth, domain-specific skill building. Starting in October 2011, the University of Minnesota, along with partners at Purdue University, the University of Oregon and Cornell University collaborated on the Data Information Literacy (DIL) 2 project to learn more about the domain-specific needs of graduate students in the area of data management education. Funded by a grant from the Institute of Museum and Library Services, each research team conducted in-depth interviews with multiple graduate students and their research advisor from five different academic science disciplines. The data management skills and needs identified across the five disciplines in the DIL project illustrated a general lack of data management training with a particular gap in skills and knowledge around long-term preservation and access of research data. 3 Our team looked at the data management needs of a research group in the structural engineering area of the civil engineering department. The results of our interviews with the civil engineers found that graduate students had the most needs in the mechanics of managing and transferring data from one student to the next and that they were particularly lacking in skills such as data documentation, access and ownership considerations, and digital preservation techniques. 4 Based on our findings, in Fall 2012 the University of Minnesota Libraries launched an instructional response to address the data management skills absent from the curriculum. This paper will outline the e-learning approach we took in planning and delivering our “Data Management Course,” a seven-module online course 5 we created using Google Sites, ScreenFlow 6 and YouTube 7 . Finally, we will discuss our plans for assessment and implementation. Literature Review The benefits of e-learning can be found enumerated in the literature reviews and discussion of many more specific studies. 8 9 The United States Department of Education was more tempered in their meta-analysis of the literature finding “Students in online conditions performed modestly better, on average, than those learning the same material through traditional face-to-face instruction.” 10 Gikandi, Morrow, and Davis’s review of formative assessment in online learning, citing the influence of Oosterhof, Conrad, & Ely, specifically posits online learning benefits students by providing “many additional opportunities to dynamically interact with and assess learners.” Gruca nicely outlines the benefits of libraries’ adopting e-learning platforms to deliver instruction. 11 Most resonant with our experience was her assertion that “E-courses are equally accessible for full-time and remote students and may be a step towards inclusion for disabled students.” We wanted our instruction to be as accessible as possible to graduate students that we anticipated would be carrying a full course load as well as a time-intensive research schedule. Although Gruca never explicitly uses the phrase, many of the benefits of elearning that she lists support the scalability of instruction inherent in an e-learning platform (Gruca states that e-learning, “saves teachers’ and students’ time” and “[o]nce published, an ecourse may be improved and used many times.”). The ability to scale out our work would be integral to ensuring future expansion at the University of Minnesota, where librarians support tens of thousands of students. Building the Course Conceptualization and creation of the course took place over the summer of 2012 by the authors and with the assistance of a library science graduate student, Kevin Cunningham. After synthesizing the findings from our graduate student interviews we decided on several learning outcomes that would meet the most pressing student needs (Table 1). The learning outcomes guided our course content creation. The DIL project emphasized outcomes that were measurable and could be assessed. Once the learning outcomes were in place, we moved into the course design phase of our project. We met face-to-face with our faculty partner to vet our intended learning outcomes and strategize how to connect students to our course content. Knowing that the graduate-level curriculum was already quite full, we knew that our approach would need to be a voluntary, extra-curricular program for students. An online, e-learning format was clearly a good fit. In addition, modularized video lessons would be easy to download and watch on any device a functionality that matched the busy graduate student lifestyle. Along with presenting practical skills in a virtual environment, the course needed a real-world application in which the students might demonstrate or test their newly acquired skills. Building on our earlier success offering data management training to researchers, we chose to use a data management plan (DMP) template as the framing device for course content delivery and evaluation. Writing a DMP, now required in all National Science Foundation grant applications, has become a skill needed by many academic researchers. As a result, each of the course modules map to a corresponding section of a data management plan template, where the student will apply what they have learned in the course. The resulting seven course modules became: