NEWSLETTER
The schools and universities are at a crossroads when it comes to students. They have more information at their disposal than ever before, but take advantage of it to boost a significant change remains a challenge. A UCLA-MIT 2022 press study found that Higher education struggles to capture and take advantage of the impact data. This digital disconnection is not only the result of obsolete systems; This is the complex network of cultural, organizational and infrastructural barriers that leave many institutions rich in data but poor information.
To discuss how institutions can convert raw data into a real impact, Edsurge spoke with Suzanne Carbonaro, vice president of postsecundarias education and workforce programs in Consortium 1edtech (1edtech). With 27 years of experience in Higher Education and Evaluation, it has served as a member of the Faculty, performed leadership roles in evaluation and accreditation, and led the curricular development promoted by competition in the Philadelphia College of Pharmacy, the oldest pharmacy school in the nation.
Edsurge: What types of data do Higher education institutions find more difficult to access and why?
Carbonaro: Despite the abundance of students' data, higher education institutions face significant challenges to access and use them effectively. The first problem is (the existence of) data silos. Learning applications, student information systems (SIS), financial aid platforms and test applications often operate independently, without communication between them. While students move fluently between these systems, their data does not. Each system exists in its own “island”, disconnected from others and from students' holistic records.
Second, there is a bad signal / noise ratio. Even when learning applications share data, much of them is not structured or lacks context. For example, random clickstream data often do not shed light on a student's learning trip. In addition, different systems can use inconsistent identifiers for the same student, which makes it difficult to track progress or connect data on all platforms.
Third, the cost of solving these problems is prohibitive for many institutions. Resting this data jungle often requires external consultants or expensive tools that many schools and universities simply cannot pay.
What key barriers prevent institutions from obtaining and using that data effectively?
Institutions fight more than just technical challenges; They also face cultural and organizational barriers. The faculty often feels judged by the analysis or decisions taken based on incomplete data. This distrust can hinder the acceptance of the adoption of new tools or processes.
Privacy concerns also play a role. Institutions must ensure that applications comply with the rigorous privacy, safety and accessibility standards before adoption. For example, IA tools must use data in a responsible manner, improving learning results without storing confidential information in patented and controlled data lakes.
Finally, institutions often do not know what questions about their students in advance. Without clear objectives or frames to use data, they run the risk of collecting information that is not processable or waiting for too much to intervene when students need support.
How can the adoption of open standards help institutions access and take advantage of that data in a more processable way?
Open standards serve as a basis for solving these challenges. Think about them as plumbing in a home: the standardized infrastructure allows you to connect any tap or device without problems. Similarly, Interoperability standards as Calibration analysis and Introperability of learning tools (LTI) Make sure edtech tools can work together without interruptions when institutions change suppliers or adopt new technologies.
For example, open standards allow institutions to track significant data of student events, such as clicks, time dedicated to tasks or questions formulated in ai tools, and contextualize it together with the holistic information of the students. This structured approach eliminates the silos and makes the data processable in real time.
In 1edtech, we create open standards that connect disparate systems with cohesive ecosystems. These standards allow institutions to change suppliers when necessary without losing access to critical data or operations interruptions.
Can you share specific examples of how access to improved data has positively affected the student's success?
In pharmaceutical education, the Faculty aligned the curricular results with the exam questions through a test platform, allowing real time monitoring of students' performance. When analyzing this data quickly, we identified students who fought with specific fundamental areas of knowledge. The linking of this information with the student's attributes helped us support students from different secondary schools or universities that needed additional help before the exam. This also allowed collaboration with these institutions to reinforce critical concepts for future cohorts.
Another example comes from our work using Comprehensive Learning Records (CLRS). When linking pharmacy skills with the key tasks in courses within the modules and allow students to see their real -time performance through CLR panels, we train them to take possession of their learning trips. Students and their mentors could see trends through months of courses, not just the qualifications, and make informed decisions about where to focus their efforts.
Currently, we are working on a subsidy of the National Foundation of Sciences of $ 20 million with the Georgia Institute of technology and other institutions to study the impact of seven different assistants deployed in online courses aimed at supporting adult students. Initially, this project faced challenges due to diverse applications that emit different data flows in separate visualization tools, without the way of combining data for longitudinal discovery. When implementing a tripod of open data standards: Edu-API, LTI and Caliper Analytics, we unify these systems in a cohesive pipe that provides contextualized ideas on the student's participation.
IA applications range from tutors that support fundamental knowledge gaps to social connection facilitators designed for online students that could otherwise feel isolated. By consolidating these tools in a reference architecture using open standards, we have allowed institutions such as Georgia tech to scale their efforts while we maintain flexibility on all platforms.
What can other institutions do now to get access to this data in a way that provides significant ideas?
Institutions can take immediate measures to improve access to processable data:
- Demand for open standards: When issuing (proposal requests) or acquiring new tools, it clear that suppliers must provide data in standardized formats such as Caliper Analytics instead of unstructured CSV files.
- Use pre -constructed pipes: For K-12 districts and other postsecundaria institutions that lack resources to build their own infrastructure, access the open standards frameworks, such as the Learning Data Reference Architecture (LDRA).
- Focus on real -time data: The collection of data based on events, such as who used what tools and how much time, combined with other key metrics, such as results -based evaluation data, allows institutional interested parties to be proactive to support their students instead of waiting for weeks to obtain information that can already be outdated.
- Ask the right questions: Instead of gathering reactive data or using intestine -based decision making, begin to identify what you want to know about your students in advance so that you can customize your learning and identify which support services need for your success.
Taking these steps nowInstitutions can create a more effective decision -making basis and student support.
What work should still be done?
While progress has been made in the construction of open architectures and pipes such as Lra, there is still a lot of work ahead:
- Foster trust: The faculty needs to ensure that the analysis is intended to support, not to judge, their teaching practices.
- Professional development: Faculty and administrators must understand why interoperability is important and how students benefit.
- Privacy standards: Institutions must continue to examine applications rigorously to obtain privacy and security problems while guaranteeing accessibility for all users.
- SCALE SOLUTIONS: Models such as LDRA should extend beyond pilot programs in large -scale implementations in various educational contexts.
1edtech is a united community committed to achieving an open, reliable and innovative educational technology ecosystem that meets the lifetime needs of each student. We join the educational community to build an integrated basis of open standards that make educational technology better for everyone, reducing complexity, accelerating innovation and the expansion of possibilities for students around the world.
