Logged in and zoned out: How laptop Internet use relates to classroom learningA new study from Michigan State University has found that Internet use can be detrimental to classroom performance. Students enrolled in an introductory psychology class at the university were asked to log into a proxy server that monitored their online activity for 15 class sessions. During the hour and 50-minute classes, participants spent a median of 37 minutes browsing the Internet for non-class-related purposes. Participants spent most of their time on social media, followed by email, shopping, watching videos, chatting, reading news, and playing games. Through looking at students’ cumulative final-exam score, the authors found that non-academic Internet use was inversely related to classroom performance. Class-related Internet use was also not associated with a benefit to classroom performance.
What if learning analytics were based on learning science?
In this article in the Australasian Journal of Educational Technology, Simon Fraser University researchers explore what learning analytics could look like if it was informed by learning science findings. The team presents six cases which reflect areas of theory and research in the learning sciences: setting goals and monitoring progress, distributed practice, retrieval practice, prior knowledge for reading, comparative evaluation of writing, and collaborative learning. Each case discusses relevant theory and proposes designs for learning analytics that support the theory or finding. According to the team, learning analytics designs “should guide students toward more effective self-regulated learning and promote motivation through perceptions of autonomy, competence, and relatedness.”
Four strategies for effective assessment in a flipped learning environment
This article from Faculty Focus looks at ways to create assessments that help “provide reliable, actionable information about student learning in the various phases of flipped learning.” The article suggests four strategies:
Start with good learning objectives: When flipping a course or unit, clear learning outcomes will help guide activities and help students understand what they need to know.
Employ a “frequent and small” approach: Short, frequent, and informative assessments can collect data on how students are doing.
Use “pre-formative” assessment: These assessments, given to students while they are learning new material independently, can provide insight into what students have learned before group activities.
Act on, and share, the data you collect: Instructors should convert the data collected into information and communicate this information with their students to help them attain their goals.
2017 NMC Horizon ReportThe New Media Consortium (NMC) and EDUCAUSE Learning Initiative have released their latest research on educational technology and its impact on higher education. The collaborative report, now in its 14th edition, details findings from the NMC Horizon Project, an ongoing research project that identifies and describes emerging technologies that will likely influence teaching and learning. The report looks at key trends, significant challenges, and important developments in educational technology. Some of the topics discussed include blended and collaborative learning, improving digital literacy, and adaptive learning technologies. The report aims to help “inform the choices that institutions are making about technology to improve, support, or extend teaching, learning, and creative inquiry in higher education across the globe.”
Five key ways to use predictive analytics to successfully address high drop-out and low completion ratesThis article from Contact North looks at ways that colleges and universities can effectively use predictive analytics. According to the article, analytics can help higher education institutions improve recruitment, retention, completion, and student engagement. To effectively use analytics, the article suggests connecting all available data about students and their behaviour, from demographics to performance on assessments. Once a prediction is made, the strategy for action should be value-driven and “needs to reflect the values, culture and supports available from the college or university.” The article also calls for investment in professional development for staff to develop institution-specific best practices. According to the article, “using our intelligence and compassion together with the predictive power of analytics can make a real difference to students and their learning.”
Designing a lab in the humanitiesFritz Breithaupt, a professor of Germanic studies at Indiana University in Bloomington, Indiana, looks at a way to make the humanities more relevant and applicable for students. Breithaupt developed the Experimental Humanities Lab, which he built to study narratives and how to improve learning and human interactions. He originally created the lab to give one student the opportunity to try hands-on experimentation. As more students began participating, Breithaupt saw it as a way for students to explore and contribute to the field. Breithaupt points out that with the limitations of the traditional classroom, it is important to inspire undergraduates and give them meaningful challenges. “The goal of our Experimental Humanities Lab is not to imitate the sciences, but to reclaim what the humanities have always done: Ask questions, observe, question our world, and, yes, experiment and gather data,” he said.
Can higher education save the web?Mike Caulfield, the director of blended and networked learning at Washington State University in Pullman, Washington, looks at how higher education is best suited to save the web. Caulfield emphasizes the need to teach students digital literacy in an age where the web has bred distracted readers. In addition to teaching students how to navigate research and books, there should also be “instruction on how to best use and critique the information environments that students inhabit on a daily basis,” he said. Caulfield suggests that the general population also needs more access to quality information and just-in-time education and advocates for open access and open educational materials. He stresses that the higher education community “must design and model new ways of working on the web…in ways that will radically transform what education looks like and will create a networked future capable of serving the common good.”
Digital badges and learning analytics provide differentiated assessment opportunities This EDUCAUSE Review article looks at how the intersection of digital badges, learning analytics, and differentiated assessment could be beneficial to learners. According to the article, both open digital badges and differentiated assessment have challenges to overcome. Open digital badges lack compelling evidence in their value, and differentiated assessment, which is at odds with standardized testing norms, has not been widely embraced. The article suggests that learning analytics can be used to create visible learning pathways that capture specific evidence of learning for badges. This information can then be used for future learning opportunities. Learning analytics can also help predict how students need to learn material and how they need to be assessed. “Used together, these three technologies can help educators target specific interventions, catalog learning evidence for future use, and provide a pathway to customize educational experiences at scale,” the authors state.