(Full disclosure: Make: Projects is partially owned by engineering.com.)
The COVID-19 pandemic left universities scrambling to find a way to continue classes. They eventually settled on remote learning, but when things are rushed, this method can quickly become flawed. Now, that the fall semester is underway, many researchers and schools are pointing to technologies like machine learning, SMS messaging, AI, and online platforms to help save the education industry.
It was widely acknowledged that the remote learning model was flawed even before the pandemic. This year marks a turning point as students and school leaders argue over the cost of education as well as the multiple models of delivery. Princeton University, Williams College, Spelman College, and American University have already discounted their tuition for a fully online education experience. With more than 50 massively open online course (MOOC) degrees available worldwide, many of them are priced cheaper than in-class courses.
The technology behind the virtual learning model is adapting to this change.
With STEM learning, it is key to have an active learning model to increase student performance, success and retention, which all originate from student engagement. Multiple studies have revealed that replacing published materials with videos, guided note-taking sheets, structured discussions, and peer instruction through labs or projects is successful in encouraging student engagement. Further, real-world and real-life problems or examples can help students better understand course content. Ultimately, it was proven that online STEM programs must be clear and concise in their instructions, but that this must be combined with engaging labs and projects.
With this in mind, universities are including AI-based chatbots to help engage and inform students about admissions, enrollment, and course deadlines through SMS messaging and the Internet. The chatbots are based on a set of preprogrammed commands while becoming smarter over time as they receive additional data from users. A user can route the chatbot responses based on certain keywords.
Using AI and machine learning, institutions are offering programs to a variety of students. Instructors can use the software to auto-grade and auto-release information to their students based on set data such as Coursera, EdX and Amesite. The software aims to grade language fluency, grammatical and syntactic correctness, vocabulary, essay length, domain information, and so on. To do this, the software checks on various grammar mistakes, word choice, techniques, style of writing, fluency, and tone using the software and instructors’ data system. The system can improve and learn over time while receiving feedback during the grading process.
Further, AI is used to optimize virtual learning models. Amesite, a cloud-based education platform, produces custom content that correlates to a student’s learning behavior with the outcomes set by the instructor. The company’s algorithms will then combine data from its educational products as well as the instructor’s feedback to build an optimized course.
Post-secondary schools have also invested in the creation of a virtual learning environment—a new transformation in online education to include supplemental material, discussion boards and virtual labs. The increased daily activity has led to an increase in student performance and engagement, especially in STEM programs. Specifically, the virtual labs have helped students demonstrate what they have learned and include open-ended discussions with their peers. The virtual labs have also helped students solve real-world issues and develop new skills, as well as improve their self-confidence, compared to a passive online educational model. These simulations and at-home labs can substitute traditional guided labs as they still result in enhanced learning outcomes and learning by failure.
Further meetings and discussions can help support the students’ education.
Software such as Make: Projects allow institutions to adapt to a virtual learning environment. The site also provides students with access to a private space where they can organize their projects or ideas with a few close friends and a public forum where they can showcase their work and receive feedback. The site also has features like project templates, group chats, teams and whiteboards.
According to Springer, it found that physics and engineering programs were successful in adapting this model since it allows students to retain the curriculum as well as engage in activities to introduce new skills. Students learn relevant conceptual topics, conduct measurements, as well as find and interpret their own data. The students were both engaged and had a deep understanding of the content compared to passive virtual models.
Programs like Make: Projects can also benefit students by providing a sense of continuity, engagement and interest, as well as supporting quantitative analysis and analytical techniques.
During this technological transformation, college leaders and policymakers must aim to create strategies to govern learning and credentialing. With the introduction of private program contracts and education firms, technological and innovative alternatives to traditional remote learning are on the rise. These can either help or hinder the education industry.
While adapting to a digital model is perhaps the only way to survive during these difficult times, policies will help ensure quality and encourage innovation, as well as help view traditional learning models through a new lens.
For more information about how online platforms can help engage students and enhance project-based learning, check out the Make: Projects latest webinar.