Building a Data Lake: Step by Step

October, 2019 During the last few years, I’ve spent most of my time helping customers assemble a variety of data sources into a data lake. Whether or not you like the idea of a data lake or a data warehouse, or a lake house, as one university administrator fondly joked, the following checklist can be useful.

Reinforcement Learning in the Classroom

May, 2019 With the chatbot in the classroom, we have the opportunity to enhance the way the classroom works. There are many examples in academic settings and commercial offerings of providing technology-driven guidance or "personalized learning." If we can offload some of the personalization workload from teachers, they can devote even more time to understanding overall class progress and providing highly specialized interventions and individualized instruction.

LTI Advantage: 5 Things You Need to Know

April, 2019 LTI Advantage provides a way to add extended capabilities to the core LTI tools and platforms. As you consider adopting LTI Advantage, here are 5 things you need to know.

AWS Lex Chatbot in the Classroom

March, 2019 Having a digital assistant in the classroom has the potential to provide significant value for both the teacher and the student. For example, rather than the teacher having to repeat answers continually, or identify resources for students individually, a digital assistant can fill this role quite effectively. The potential to provide significant value assumes that the system's developer understands the types of problems that automation can solve, and that the school has the resources to invest in its implementation. If some small timesavers can be identified, schools with technical resources can leverage a chatbot in their classrooms.

uPortal 5.0: Up & Running!

October, 2017 A new era in the story of Apereo uPortal is dawning: the era of uPortal 5. This new chapter brings many profound changes to uPortal. From my perspective, this new major version (version 5) is significantly more different from its precursor (version 4) than version 4 was from version 3. In fact, I would say this change (from 4 to 5) is more significant than any new major version since version 2.

Academic versus Administrative Computing: Bridging the Gap - "Recommendations" (Article #4)

October, 2017 As we explored earlier in this article series, "Separate Evolution of Two Systems" and "The Impact of Data on Student Success," disconnects between the two sides of campus computing, academic and administrative, can impact efforts to monitor and improve student success. And institutions today face mounting pressure to choose from a variety of solutions that help to mitigate or minimize this disconnect (see, "Possible Solutions"). Short of undertaking massive efforts to consolidate and centralize data systems for institutions, what is the best way to bridge the gap between existing systems in order to minimize negative impact?

Academic vs. Administrative Computing: Bridging the Gap - "Possible Solutions" (Article #3)

September, 2017 In the first two articles of this series, "Separate Evolution of Two Systems" and "The Impact of Data on Student Success," we focused on the disconnect between the two sides of campus computing, academic and administrative, examining the impact of the separate evolution of these systems on student success. One of the most significant impacts of these compartmentalized systems is the difficulty to put data together to see a holistic picture of the student. Today, there is increasing awareness that a holistic view of student performance, based on accurate data, can positively impact student success.

Academic vs. Administrative Computing: Bridging the Gap - "The Impact of Data on Student Success" (Article #2)

June, 2017 If academic (LMS) and administrative (SIS) systems can coexist, each serving their own unique purpose, what's wrong with having different systems at the end of the day? There is certainly a good reason to keep a separation of concerns - why, for example, should learning systems have to worry about keeping track of a student's financial record or incoming test scores? Conversely, why should a back-end student information system (SIS) invest in keeping tabs on the student's learning experience?

Learning Analytics Adoption and Implementation Trends: Quantitative Analysis of Organizational and Technical Trends

June, 2016 For many institutions, the idea of beginning a learning analytics initiative may seem overwhelming and complex. There is often the perception that too much work needs to be done before any type of initiative can be explored. You might be surprised to learn that most institutions are already prepared for some type of learning analytics initiative. Whether your institution is ready to use student data and visualize it on a dashboard, or even pursue a small-scale pilot, the quantitative and qualitative analysis of organizational and technical trends supports an overall sense of institutional readiness for learning analytics.