Top 122 Learning Analytics Free Questions to Collect the Right answers

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 122 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:

Nurse Learning Analytics leadership and clarify ways to gain access to competitive Learning Analytics services.

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

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

– What is Effective Learning Analytics?

Academic analytics Critical Criteria:

Investigate Academic analytics tactics and gather practices for scaling Academic analytics.

– A compounding model resolution with available relevant data can often provide insight towards a solution methodology; which Learning Analytics models, tools and techniques are necessary?

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

– What are the business goals Learning Analytics is aiming to achieve?

Artificial intelligence Critical Criteria:

Add value to Artificial intelligence visions and track iterative Artificial intelligence results.

– Do we cover the five essential competencies-Communication, Collaboration,Innovation, Adaptability, and Leadership that improve an organizations ability to leverage the new Learning Analytics in a volatile global economy?

Big data Critical Criteria:

See the value of Big data outcomes and prioritize challenges of Big data.

– From all data collected by your organization, what is approximately the share of external data (collected from external sources), compared to internal data (produced by your operations)?

– Do you see the need for actions in the area of standardisation (including both formal standards and the promotion of/agreement on de facto standards) related to your sector?

– Looking at hadoop big data in the rearview mirror, what would you have done differently after implementing a Data Lake?

– Do you see regulatory restrictions on data/servers localisation requirements as obstacles for data-driven innovation?

– Does your organization share data with other entities (with customers, suppliers, companies, government, etc)?

– Can we measure the basic performance measures consistently and comprehensively?

– How close to the edge can we push the filtering and compression algorithms?

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

– Does your organization have a strategy on big data or data analytics?

– Is the need persistent enough to justify development costs?

– How fast can we determine changes in the incoming data?

– Wait, DevOps does not apply to Big Data?

– What are some impacts of Big Data?

– What is collecting all this data?

– Is Big data different?

– what is Different about Big Data?

– How to deal with too much data?

– What is Advanced Analytics?

– What can it be used for?

Business intelligence Critical Criteria:

Debate over Business intelligence results and question.

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

– Can you easily add users and features to quickly scale and customize to your organizations specific needs?

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

– What are the approaches to handle RTB related data 100 GB aggregated for business intelligence?

– What is the difference between a data scientist and a business intelligence analyst?

– Does your bi solution allow analytical insights to happen anywhere and everywhere?

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

– What are the best UI frameworks for Business Intelligence Applications?

– What information needs of managers are satisfied by the new BI system?

– Describe the process of data transformation required by your system?

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

– What social media dashboards are available and how do they compare?

– Does your BI solution require weeks or months to deploy or change?

– What are the trends shaping the future of business analytics?

– How would you broadly categorize the different BI tools?

– Can users easily create these thresholds and alerts?

– Is the product accessible from the internet?

– Will your product work from a mobile device?

– Business Intelligence Tools?

– How are you going to manage?

Collaborative filtering Critical Criteria:

Huddle over Collaborative filtering management and figure out ways to motivate other Collaborative filtering users.

– How do senior leaders actions reflect a commitment to the organizations Learning Analytics values?

– Are there any disadvantages to implementing Learning Analytics? There might be some that are less obvious?

– How can skill-level changes improve Learning Analytics?

Content analysis Critical Criteria:

Sort Content analysis adoptions and define what do we need to start doing with Content analysis.

– What is the total cost related to deploying Learning Analytics, including any consulting or professional services?

– How do mission and objectives affect the Learning Analytics processes of our organization?

– How would one define Learning Analytics leadership?

Content management system Critical Criteria:

Investigate Content management system adoptions and know what your objective is.

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

– Are there recognized Learning Analytics problems?

– What is a learning management system?

– How do we define online learning?

– Is Learning Analytics Required?

Data mining Critical Criteria:

Brainstorm over Data mining planning and slay a dragon.

– 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?

– What other jobs or tasks affect the performance of the steps in the Learning Analytics process?

– 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?

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

– Does Learning Analytics appropriately measure and monitor risk?

– What programs do we have to teach data mining?

Educational data mining Critical Criteria:

Bootstrap Educational data mining governance and report on developing an effective Educational data mining strategy.

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

– Is there any existing Learning Analytics governance structure?

Google analytics Critical Criteria:

Analyze Google analytics risks and find out.

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

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

Information visualization Critical Criteria:

Consolidate Information visualization quality and simulate teachings and consultations on quality process improvement of Information visualization.

– Do we monitor the Learning Analytics decisions made and fine tune them as they evolve?

– Does our organization need more Learning Analytics education?

Intelligent tutoring system Critical Criteria:

Audit Intelligent tutoring system visions and mentor Intelligent tutoring system customer orientation.

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

– What is the source of the strategies for Learning Analytics strengthening and reform?

– What sources do you use to gather information for a Learning Analytics study?

Management information systems Critical Criteria:

Exchange ideas about Management information systems issues and summarize a clear Management information systems focus.

– What are the barriers to increased Learning Analytics production?

– How do we Lead with Learning Analytics in Mind?

– Why are Learning Analytics skills important?

Master of Science Critical Criteria:

Reconstruct Master of Science issues and look in other fields.

– Why is Learning Analytics important for you now?

– What are the long-term Learning Analytics goals?

Odds algorithm Critical Criteria:

Focus on Odds algorithm management and differentiate in coordinating Odds algorithm.

– What role does communication play in the success or failure of a Learning Analytics project?

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

Online education Critical Criteria:

Consider Online education tactics and point out improvements in Online education.

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

– How do we Identify specific Learning Analytics investment and emerging trends?

Operational research Critical Criteria:

Wrangle Operational research leadership and proactively manage Operational research risks.

– Which individuals, teams or departments will be involved in Learning Analytics?

Pattern recognition Critical Criteria:

Brainstorm over Pattern recognition visions and pioneer acquisition of Pattern recognition systems.

Personal learning environment Critical Criteria:

Define Personal learning environment strategies and finalize specific methods for Personal learning environment acceptance.

– When a Learning Analytics manager recognizes a problem, what options are available?

– What are current Learning Analytics Paradigms?

Predictive analytics Critical Criteria:

Have a meeting on Predictive analytics engagements and improve Predictive analytics service perception.

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

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

– Have all basic functions of Learning Analytics been defined?

– What threat is Learning Analytics addressing?

Social network analysis Critical Criteria:

Group Social network analysis quality and grade techniques for implementing Social network analysis controls.

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

– What are the success criteria that will indicate that Learning Analytics objectives have been met and the benefits delivered?

– Is the Learning Analytics organization completing tasks effectively and efficiently?

Social network analysis software Critical Criteria:

Drive Social network analysis software tasks and cater for concise Social network analysis software education.

– What are your results for key measures or indicators of the accomplishment of your Learning Analytics strategy and action plans, including building and strengthening core competencies?

– what is the best design framework for Learning Analytics organization now that, in a post industrial-age if the top-down, command and control model is no longer relevant?

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

Student information system Critical Criteria:

Contribute to Student information system risks and forecast involvement of future Student information system projects in development.

Text analytics Critical Criteria:

Study Text analytics tasks and get out your magnifying glass.

– At what point will vulnerability assessments be performed once Learning Analytics is put into production (e.g., ongoing Risk Management after implementation)?

– Among the Learning Analytics product and service cost to be estimated, which is considered hardest to estimate?

– Have text analytics mechanisms like entity extraction been considered?

Virtual learning environment Critical Criteria:

Examine Virtual learning environment goals and adopt an insight outlook.

– How do you determine the key elements that affect Learning Analytics workforce satisfaction? how are these elements determined for different workforce groups and segments?

– How to Secure Learning Analytics?

Web analytics Critical Criteria:

Scan Web analytics failures and ask what if.

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

– 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 |

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) …

Watershed | Learning Analytics for Organizations

Deep Learning Analytics

Academic analytics External links:

ERIC – Signals: Applying Academic Analytics, …

What We Do – Academic Analytics

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

Artificial intelligence External links:

Robotics & Artificial Intelligence ETF – Global X Funds

Simple examples of Artificial Intelligence – Stack Exchange

Top 15 Artificial Intelligence ETFs –

Big data External links:

Event Hubs – Cloud big data solutions | Microsoft Azure

Big Data and Advanced Analytics Solutions | Microsoft Azure

Business intelligence External links:

Business Intelligence Tools & Software | Square

Business Intelligence Software – ERP & Project …

Business Intelligence | Microsoft

Collaborative filtering External links:

Collaborative Filtering | Recommender Systems

Content analysis External links:

Vision API – Image Content Analysis | Google Cloud Platform

[PDF]An Introduction to Content Analysis

Content Analysis – SEO Review Tools

Content management system External links:

Content Management System – Cognizant

HR Pilot – ePlace Solutions Content Management System

CGS – Content Management System

Data mining External links:

Analytics and Data Mining Programs

Nebraska Oil and Gas Conservation Commission – GIS Data Mining

UT Data Mining

Educational data mining External links:

Educational Data Mining 2018 – July 15-18, 2018, Buffalo NY

Why is Educational Data Mining Important? – YouTube

Google analytics External links:

Google Analytics Solutions – Marketing Analytics & …

Google Analytics

Google Analytics | Google Developers

Information visualization External links:

Information visualization (Book, 2001) []

Intelligent tutoring system External links:

Intelligent Tutoring System – YouTube

Intelligent Tutoring System – YouTube

Management information systems External links:

Management Information Systems Major – FSU

Management Information Systems (MIS) – …

Management information systems (Book, 2017) …

Master of Science External links:

Master of Science in Marketing Research Program | …

Master of science in Operations Management | …

Master of Science in Analytics | Georgetown University

Odds algorithm External links:


LEAKED: FIFA 18’s Ultimate Team Pack Odds Algorithm

odds algorithm | Eventually Almost Everywhere

Online education External links:

Online Education Degrees | Ashford University

Online Degrees in Tennessee | Online Education | TN eCampus

Online Education – Cancer Registry

Operational research External links:

Journal of the Operational Research Society: Vol 69, No 4

ORC- Operational Research Consultants, Inc

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.

Pattern recognition External links:

Pattern Recognition – MATLAB & Simulink – MathWorks

Mike the Knight Potion Practice: Pattern Recognition

Tradable Patterns – Trade Better with Pattern Recognition

Personal learning environment External links:

Personal Learning Environment – What is PLE? In 60 …

EDU510 – Cassandra Spicer’s Personal Learning Environment

EDU505 – Personal Learning Environment

Predictive analytics External links:

Strategic Location Management & Predictive Analytics | …

Predictive Analytics Solutions for Global Industry | Uptake

Predictive Analytics Software, Social Listening | NewBrand

Social network analysis External links:

Good book on Social Network Analysis basics and as an intro to this area of research. But someone doing a research project in this area would require a more in-depth guide. The book provides some different approaches and mentions some software options including Pajek, UNICET, and SIENA, so this section may not be as useful if you are …

Social network analysis software External links:

NetMiner – Social Network Analysis Software

NetMiner – Social Network Analysis Software

Social Network Analysis Software – NetMiner : 3.5.3 …

Student information system External links:

Student Information System | Portal

ASISTS | Adult Student Information System & Technical …

My Integrated Student Information System / New MiSiS …

Text analytics External links:

Text analytics software| NICE LTD | NICE

Provalis Research | Text Analytics Software Leader

Text Analytics | What is Text Analytics? – Clarabridge

Virtual learning environment External links:

Welcome to the NCPro Virtual Learning Environment

MSE Virtual Learning Environment

Our Virtual Learning Environment

Web analytics External links:

Careers | Mobile & Web Analytics | Mixpanel

11 Best Web Analytics Tools |

Web Analytics in Real Time | Clicky