114 In-Depth Learning Analytics Questions for Professionals

What is involved in Learning Analytics

Find out what the related areas are that Learning Analytics connects with, associates with, correlates with or affects, and which require thought, deliberation, analysis, review and discussion. This unique checklist stands out in a sense that it is not per-se designed to give answers, but to engage the reader and lay out a Learning Analytics thinking-frame.

How far is your company on its Learning Analytics journey?

Take this short survey to gauge your organization’s progress toward Learning Analytics leadership. Learn your strongest and weakest areas, and what you can do now to create a strategy that delivers results.

To address the criteria in this checklist for your organization, extensive selected resources are provided for sources of further research and information.

Start the Checklist

Below you will find a quick checklist designed to help you think about which Learning Analytics related domains to cover and 114 essential critical questions to check off in that domain.

The following domains are covered:

Learning Analytics, Academic analytics, Artificial intelligence, Big data, Business intelligence, Collaborative filtering, Content analysis, Content management system, Data mining, Educational data mining, Google analytics, Information visualization, Intelligent tutoring system, Management information systems, Master of Science, Odds algorithm, Online education, Operational research, Pattern recognition, Personal learning environment, Predictive analytics, Social network analysis, Social network analysis software, Student information system, Text analytics, Virtual learning environment, Web analytics:

Learning Analytics Critical Criteria:

Align Learning Analytics adoptions and integrate design thinking in Learning Analytics innovation.

– Think about the functions involved in your Learning Analytics project. what processes flow from these functions?

– Does Learning Analytics analysis show the relationships among important Learning Analytics factors?

– How would one define Learning Analytics leadership?

Academic analytics Critical Criteria:

Distinguish Academic analytics issues and find answers.

– What is the purpose of Learning Analytics in relation to the mission?

– What are the usability implications of Learning Analytics actions?

Artificial intelligence Critical Criteria:

Accommodate Artificial intelligence outcomes and know what your objective is.

– What are your current levels and trends in key measures or indicators of Learning Analytics product and process performance that are important to and directly serve your customers? how do these results compare with the performance of your competitors and other organizations with similar offerings?

– Is maximizing Learning Analytics protection the same as minimizing Learning Analytics loss?

– Have the types of risks that may impact Learning Analytics been identified and analyzed?

Big data Critical Criteria:

Consider Big data visions and stake your claim.

– From all the data collected by your organization, what is approximately the percentage that is further processed for value generation?

– What is (or would be) the added value of collaborating with other entities regarding data sharing in your sector?

– What rules and regulations should exist about combining data about individuals into a central repository?

– In which area(s) do data integration and BI, as part of Fusion Middleware, help our IT infrastructure?

– Does big data threaten the traditional data warehouse business intelligence model stack?

– what is needed to build a data-driven application that runs on streams of fast and big data?

– In which way does big data create, or is expected to create, value in the organization?

– What new definitions are needed to describe elements of new Big Data solutions?

– What if the needle in the haystack happens to be a complex data structure?

– How can the benefits of Big Data collection and applications be measured?

– What is the contribution of subsets of the data to the problem solution?

– Does your organization have the necessary skills to handle big data?

– Are our business activities mainly conducted in one country?

– How much data is really relevant to the problem solution?

– Which other Oracle products are used in your solution?

– How do we measure value of an analytic?

– Why are we collecting all this data?

– Hash tables for term management?

– What is Advanced Analytics?

– Find traffic bottlenecks ?

Business intelligence Critical Criteria:

Confer over Business intelligence issues and look at the big picture.

– Does the software let users work with the existing data infrastructure already in place, freeing your IT team from creating more cubes, universes, and standalone marts?

– Choosing good key performance indicators (KPI Key Performance Indicators) did we start from the question How do you measure a companys success?

– As we develop increasing numbers of predictive models, then we have to figure out how do you pick the targets, how do you optimize the models?

– Does your mobile solution allow you to interact with desktop-authored dashboards using touchscreen gestures like taps, flicks, and pinches?

– Does a BI business intelligence CoE center of excellence approach to support and enhancements benefit our organization and save cost?

– Can your software connect to all forms of data, from text and Excel files to cloud and enterprise-grade databases, with a few clicks?

– Does your bi solution require weeks of training before new users can analyze data and publish dashboards?

– What is the future scope for combination of Business Intelligence and Cloud Computing?

– Was your software written by your organization or acquired from a third party?

– How will you know that the Learning Analytics project has been successful?

– What is your anticipated learning curve for technical administrators?

– Can your bi solution quickly locate dashboard on your mobile device?

– What is the process of data transformation required by your system?

– What type and complexity of system administration roles?

– Are there any on demand analytics tools in the cloud?

– Can your product map ad-hoc query results?

– Do you still need a data warehouse?

– Do you offer formal user training?

– Do you support video integration?

Collaborative filtering Critical Criteria:

Bootstrap Collaborative filtering management and separate what are the business goals Collaborative filtering is aiming to achieve.

– What are the key elements of your Learning Analytics performance improvement system, including your evaluation, organizational learning, and innovation processes?

– What knowledge, skills and characteristics mark a good Learning Analytics project manager?

– What are the Essentials of Internal Learning Analytics Management?

Content analysis Critical Criteria:

Reorganize Content analysis adoptions and probe the present value of growth of Content analysis.

– How do we measure improved Learning Analytics service perception, and satisfaction?

– How do we know that any Learning Analytics analysis is complete and comprehensive?

Content management system Critical Criteria:

Refer to Content management system governance and secure Content management system creativity.

– What vendors make products that address the Learning Analytics needs?

– Who sets the Learning Analytics standards?

– What is a learning management system?

– How do we define online learning?

Data mining Critical Criteria:

See the value of Data mining governance and suggest using storytelling to create more compelling Data mining projects.

– Do you see the need to clarify copyright aspects of the data-driven innovation (e.g. with respect to technologies such as text and data mining)?

– What types of transactional activities and data mining are being used and where do we see the greatest potential benefits?

– How can you negotiate Learning Analytics successfully with a stubborn boss, an irate client, or a deceitful coworker?

– What is the difference between Data Analytics Data Analysis Data Mining and Data Science?

– What is the difference between business intelligence business analytics and data mining?

– What new services of functionality will be implemented next with Learning Analytics ?

– Is business intelligence set to play a key role in the future of Human Resources?

– Does our organization need more Learning Analytics education?

– What programs do we have to teach data mining?

Educational data mining Critical Criteria:

Disseminate Educational data mining goals and summarize a clear Educational data mining focus.

– What may be the consequences for the performance of an organization if all stakeholders are not consulted regarding Learning Analytics?

– Who will provide the final approval of Learning Analytics deliverables?

Google analytics Critical Criteria:

See the value of Google analytics goals and catalog what business benefits will Google analytics goals deliver if achieved.

– Risk factors: what are the characteristics of Learning Analytics that make it risky?

– Is Supporting Learning Analytics documentation required?

– What is Effective Learning Analytics?

Information visualization Critical Criteria:

Brainstorm over Information visualization outcomes and devise Information visualization key steps.

– What tools do you use once you have decided on a Learning Analytics strategy and more importantly how do you choose?

– How does the organization define, manage, and improve its Learning Analytics processes?

– What are the barriers to increased Learning Analytics production?

Intelligent tutoring system Critical Criteria:

Explore Intelligent tutoring system results and correct Intelligent tutoring system management by competencies.

– Who is responsible for ensuring appropriate resources (time, people and money) are allocated to Learning Analytics?

– Can Management personnel recognize the monetary benefit of Learning Analytics?

Management information systems Critical Criteria:

Pay attention to Management information systems visions and plan concise Management information systems education.

– Does Learning Analytics create potential expectations in other areas that need to be recognized and considered?

– How will we insure seamless interoperability of Learning Analytics moving forward?

– What potential environmental factors impact the Learning Analytics effort?

Master of Science Critical Criteria:

Detail Master of Science adoptions and be persistent.

– Are there any easy-to-implement alternatives to Learning Analytics? Sometimes other solutions are available that do not require the cost implications of a full-blown project?

– Is there a Learning Analytics Communication plan covering who needs to get what information when?

– Who is the main stakeholder, with ultimate responsibility for driving Learning Analytics forward?

Odds algorithm Critical Criteria:

Consider Odds algorithm tasks and probe the present value of growth of Odds algorithm.

– For your Learning Analytics project, identify and describe the business environment. is there more than one layer to the business environment?

– Will Learning Analytics deliverables need to be tested and, if so, by whom?

Online education Critical Criteria:

Map Online education planning and give examples utilizing a core of simple Online education skills.

– How do we ensure that implementations of Learning Analytics products are done in a way that ensures safety?

– Does Learning Analytics analysis isolate the fundamental causes of problems?

– Who needs to know about Learning Analytics ?

Operational research Critical Criteria:

Grade Operational research projects and research ways can we become the Operational research company that would put us out of business.

– Think about the kind of project structure that would be appropriate for your Learning Analytics project. should it be formal and complex, or can it be less formal and relatively simple?

Pattern recognition Critical Criteria:

Accelerate Pattern recognition adoptions and handle a jump-start course to Pattern recognition.

– What is our Learning Analytics Strategy?

Personal learning environment Critical Criteria:

Co-operate on Personal learning environment results and stake your claim.

– What are your key performance measures or indicators and in-process measures for the control and improvement of your Learning Analytics processes?

– Think of your Learning Analytics project. what are the main functions?

– Do we have past Learning Analytics Successes?

Predictive analytics Critical Criteria:

Graph Predictive analytics goals and report on the economics of relationships managing Predictive analytics and constraints.

– Why is it important to have senior management support for a Learning Analytics project?

– Meeting the challenge: are missed Learning Analytics opportunities costing us money?

– What tools and technologies are needed for a custom Learning Analytics project?

– What are direct examples that show predictive analytics to be highly reliable?

Social network analysis Critical Criteria:

Align Social network analysis decisions and devise Social network analysis key steps.

– What are the disruptive Learning Analytics technologies that enable our organization to radically change our business processes?

– What are internal and external Learning Analytics relations?

Social network analysis software Critical Criteria:

Detail Social network analysis software issues and customize techniques for implementing Social network analysis software controls.

– What about Learning Analytics Analysis of results?

Student information system Critical Criteria:

Brainstorm over Student information system management and customize techniques for implementing Student information system controls.

– How do your measurements capture actionable Learning Analytics information for use in exceeding your customers expectations and securing your customers engagement?

– Who will be responsible for deciding whether Learning Analytics goes ahead or not after the initial investigations?

Text analytics Critical Criteria:

Give examples of Text analytics leadership and ask questions.

– Will Learning Analytics have an impact on current business continuity, disaster recovery processes and/or infrastructure?

– Have text analytics mechanisms like entity extraction been considered?

– What are the long-term Learning Analytics goals?

Virtual learning environment Critical Criteria:

Rank Virtual learning environment planning and acquire concise Virtual learning environment education.

– Where do ideas that reach policy makers and planners as proposals for Learning Analytics strengthening and reform actually originate?

– Are there Learning Analytics Models?

Web analytics Critical Criteria:

See the value of Web analytics risks and transcribe Web analytics as tomorrows backbone for success.

– What statistics should one be familiar with for business intelligence and web analytics?

– What are the Key enablers to make this Learning Analytics move?

– How is cloud computing related to web analytics?


This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the Learning Analytics Self Assessment:


Author: Gerard Blokdijk

CEO at The Art of Service | http://theartofservice.com



Gerard is the CEO at The Art of Service. He has been providing information technology insights, talks, tools and products to organizations in a wide range of industries for over 25 years. Gerard is a widely recognized and respected information expert. Gerard founded The Art of Service consulting business in 2000. Gerard has authored numerous published books to date.

External links:

To address the criteria in this checklist, these selected resources are provided for sources of further research and information:

Learning Analytics External links:

Learning Analytics Explained. (eBook, 2017) [WorldCat.org]

Academic analytics External links:

Praestantia Research: Academic Analytics


12 Academic Analytics reviews. A free inside look at company reviews and salaries posted anonymously by employees.

Artificial intelligence External links:

Logojoy | Artificial Intelligence Logo Design

Big data External links:

ZestFinance.com: Machine Learning & Big Data Underwriting

Loudr: Big Data for Music Rights

Take 5 Media Group – Build an audience using big data

Business intelligence External links:

Business Intelligence and Big Data Analytics Software

Mortgage Business Intelligence Software :: Motivity Solutions

Collaborative filtering External links:

Collaborative Filtering | Recommender Systems

Content analysis External links:

Content Analysis – SEO Review Tools

Content analysis (eBook, 2015) [WorldCat.org]

[PDF]Three Approaches to Qualitative Content Analysis – …

Content management system External links:

Content Management System – Cognizant

CGS – Content Management System

MARPHTC Learning Content Management System

Data mining External links:

UT Data Mining

Data Mining Extensions (DMX) Reference | Microsoft Docs

Data mining | computer science | Britannica.com

Educational data mining External links:

[PDF]Learning Analytics and Educational Data Mining: …
http://www.columbia.edu/~rsb2162/LAKs reformatting v2.pdf

[PDF]Student Privacy and Educational Data Mining: …

Educational Data Mining: A Review – ScienceDirect

Google analytics External links:

Google Analytics Solutions – Marketing Analytics & …

Google Analytics

Enterprise Marketing Analytics – Google Analytics 360 Suite

Information visualization External links:

Information visualization (Book, 2001) [WorldCat.org]

Information Visualization: What is Information Visualization?

Management information systems External links:

What is MIS? | Management Information Systems

Management information systems (Book, 2011) …

Master of Science External links:

Master of Science Degrees | GTPE – Georgia Tech Online

Master of Science in Nursing – Department of Nursing

Master of Science in Nursing | Rutgers School of Nursing

Odds algorithm External links:


odds algorithm | Eventually Almost Everywhere

Online education External links:

Online Education Degrees | Ashford University

Online Education – Cancer Registry

Operational research External links:

Operations Research (O.R.), or operational research in the U.K, is a discipline that deals with the application of advanced analytical methods to help make better decisions.
http://Reference: informs.org/about-informs/what-is-operations-research

ORC- Operational Research Consultants, Inc

Pattern recognition External links:

Mike the Knight Potion Practice: Pattern Recognition

Dora’s Ballet Adventure Game: Pattern Recognition – Nick Jr.

Personal learning environment External links:

Ayans Personal Learning Environment – Failure is …

Ernesto’s Personal Learning Environment

Personal Learning Environment – Alyssa Barrett

Predictive analytics External links:

Strategic Location Management & Predictive Analytics | Tango

Inventory Optimization for Retail | Predictive Analytics

Predictive Analytics Solutions for Global Industry | Uptake

Social network analysis External links:

[PDF]Social Network Analysis – mjdenny.com

Optimizing Social Network Analysis | CTTSO – tswg.gov

NodeXL | Your Social Network Analysis Tool for Social Media

Social network analysis software External links:

NetMiner – Social Network Analysis Software

Student information system External links:

ASISTS | Adult Student Information System & Technical …

Rensselaer’s Student Information System

openSIS Student Information System

Text analytics External links:

Text analytics software| NICE LTD | NICE

The Truth about Text Analytics and Sentiment Analysis

[PDF]Syllabus Course Title: Text Analytics – Regis University

Virtual learning environment External links:

Case Study: Marriott virtual learning environment | ON24

MSE Virtual Learning Environment

Web analytics External links:

Careers | Mobile & Web Analytics | Mixpanel

AFS Analytics – Web analytics

Web analytics | HitsLink

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