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K–12 Adaptive Diagnostic
I used i-Ready when I taught 7th grade mathematics.
https://www.curriculumassociates.com/products/iready/diagnostic-instruction.aspx

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My district used Schoolnet for our quarter tests and I used it for pre-tests and unit tests.  "Test administration system supports the creation, management, administration, monitoring, and data collection of large-scale, quality, higher-order thinking, standards-aligned, district-administered or classroom assessments to meet a variety of benchmarking and formative assessment goals. Reporting tools consolidate assessment results with data pulled from your SIS, including demographics, attendance, course marks, discipline, longitudinal assessment data, and much more." (Pearson, 2018, para. 2-3).

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"According to the 1st International Conference on Learning Analytics and Knowledge, 'learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for the purposes of understanding and optimizing learning and the environments in which it occurs'" (Long & Siemens, 2011, p 34)

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I went to this workshop and I can see using a tool like this in my future training/ID role to show the value of the training.

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Image retrieved from this article: https://www.td.org/insights/learning-analytics-what-does-data-science-have-to-do-with-learning

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Image retrieved from: https://events.educause.edu/special-topic-events/nercomp-annual-conference/2016/proceedings/analytics-in-instructional-design

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Introduction to Learning Analytics Video

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Introduction to Learning Analytics Video

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This video comes from an edX course on Learning Analytics Fundamentals

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Week 1: Introduction to Learning Analytics

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"into what is happening in the learning process and suggest ways in which educators can make improvements" (Long & Siemens, 2011, p. 32)

"into which students are at risk of dropping out or need additional support to increase their success, and confidence in the learning process" (Long & Siemens, 2011, p.32)

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"data in real time, making it possible to process and act on it instantaneously" (Long & Siemens, 2011, p. 34)

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Big Data, the Science of Learning, Analytics, and Transformation of Education

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Big Data, the Science of Learning, Analytics, and Transformation of Education

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Big Data, the Science of Learning, Analytics, and Transformation of Education

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"Save money, enhancing student achievement, planning courses, recruiting and retaining students, optimizing the scheduling of classrooms, and maximizing alumni donations" (Barneveld, Arnold, & Campbell, 2012, p. 2)

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Personalized learning to students needs.

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The Importance of Learning Analytics in Instructional Design

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The Importance of Learning Analytics in Instructional Design

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According to Jim Yupangco (2017), "most instructors leverage LA for activities like the following:

Monitoring student progress.

Exploring student data.

Spotting problems and discovering patterns.

Finding early indicators for success or failure.

Assessing the usefulness of learning materials.

Intervening and helping struggling students.

Improving their teaching."

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Learning Analytics In Instructional Design

Every time a student interacts with your Learning Management System, another piece of data is created and collected. Every login, button click, chat entry, assessment, and time stamp is tracked and recorded. Many Instructional Designers don't take full advantage of this data-but with learning analytics (LA), you can use that data in powerful ways to impact not only your course design, but much more.

Educators use analytics as a source of feedback, which they can use to tweak their courses [1]. Most instructors leverage LA for activities like the following:

Monitoring student progress.

Exploring student data.

Spotting problems and discovering patterns.

Finding early indicators for success or failure.

Assessing the usefulness of learning materials.

Intervening and helping struggling students.

Improving their teaching.

But the importance of learning analytics in Instructional Design goes far beyond tactical module improvements. LA provides some enormous benefits to learners, course design, and the organization itself.

In this article, we'll explore the impact that learning analytics can have on learners, course design, and the broader organization itself.

Impact On Learners

Because learning data captures everything a student does online, it's possible to create "smart" algorithms that can sense when a student is struggling, based on their behavior. It's even possible to make early predictions about long-term outcomes. Models that use LA can:

Identify if a student is disengaged with the course material.

Predict student achievement.

Understand how particular students use different learning resources.

Many LMSs can use this learning analytics data to create personalized learning experiences that are customized for each student, based on their behaviors and performance results [2]. Online courses can be personalized in a couple ways:

Providing options that let learners tailor their learning experience to their preferences. For example, some systems allow students to choose the next topic to work on, or to pick the type of learning activity they like best (video instruction, reading instruction, practice, self-test, etc.).

Adapting to the learner's needs based on their performance. This is more common. Typically, it involves assessing the student's competence or mastery, and providing the appropriate level of learning content-such as prerequisite material or advanced subject matter-depending on the student's readiness.

For that matter, many systems can even detect when a student is "gaming the system"-taking advantage of the Learning Management System to succeed without putting in the effort to learn. Other models can infer learners' emotions based on their performance and behavior. The system responds with appropriate tones-supportive for strugglers, sarcastic toward slackers.

Some researchers believe that LA can be used to identify students who are at risk of becoming disengaged, failing, or dropping out of the course. Learning Management Systems can track key indicators, such as forum participation and completed assessments, to calculate a risk score. Widgets such as the Moodle Engagement Analytics Plugin (MEAP) can alert instructors of students that may be headed for failure or dropout. This gives instructors the chance to provide extra help and increase retention.

Impact On Course Design

Learning analytics uses a wide range of data about learners and their behaviors. You can use this data to help design the best learning environment and experience for your students.

There is tremendous potential in the mountains of data that's collected to better understand how students learn. So far, most of the research has focused on developing models for predicting success and retention. But by analyzing students' behaviors online, it's possible to get a better understanding of what environments and experiences are best suited for learning.

There's a push to discover a generalized model for predicting student success. But some research suggests that the differences between contexts and courses play a major role in effectively predicting whether students will pass or fail [3]. LA can make it possible to understand the contextual variables from course to course, and help Instructional Designers develop learning modules that take those factors into account.

This provides great potential for understanding and optimizing the learning process. By tracking learners' interactions with the LMS, instructors can pinpoint the most effective techniques and enhance their courses accordingly. (identify the success of their pedagogies).

Gathering more complete data on the student experience can also help your company to spot areas of improvement that students are concerned about-for example, inadequate feedback. These interventions can help instructors build a better course that serves learners' needs more fully [4].

Impact On The Organization

As improved course designs impact students' success, you can begin to leverage learning analytics to track the impact on your company's operational efficiency.

The Kirkpatrick Evaluation Model and the related Phillips' model were developed to evaluate the effectiveness of online learning based on the impact it has on your organization. But the challenge for many companies is being able to isolate online learning from all the other factors in your company-factors like process improvements, new productivity apps, or culture change.

While it's impossible to completely isolate the effectiveness of online learning from all other factors in your organization, you can take a broad systems approach and use LA as one of many factors that measure the overall effectiveness of your training and development program [5].

LA can have another, indirect impact on your organization, as well. For some companies, learning analytics has a ripple effect throughout the business. As Instructional Designers increasingly use LA to make better decisions about their course design, other areas of your organization may see the benefits of data-driven decision-making. Before long, they may begin to adopt the practice in their own spheres-increasing the overall efficiency of your company.

Taking Advantage Of Learning Analytics In Instructional Design

Your Learning Management System is automatically tracking and recording all the data you need. The era of big data makes it easy to access anything related to your students' learning behaviors. Taking advantage of learning analytics gives you a tremendous opportunity to make an impact that goes beyond merely tweaking your online modules. Learning analytics can help you make Instructional Design improvements that affect your learners, the courses themselves, and your organization.

Ready to go deeper in your course design and Learning Management System mastery? Check out our upcoming webinars!

References

1. Learning design and learning analytics: building the links

2. Using Learning Analytics in Personalized Learning

3. Learning analytics should not promote one size fits all: The effects of instructional conditions in predicting academic success

4. Learning analytics in higher education

5. Learning Analytics that Maximize Business Impact

Related Articles:

1. Free eBook: Advanced Reporting In Moodle & Totara, With Zoola Analytics

2. 3 Tips To Turn Learning Analytics Into Actionable Outcomes

3. 7 Ethical Concerns With Learning Analytics

4. What Sources Of Learning Analytics Should You Be Collecting?

5. Learning Metrics That Matter: Data Points You Should Be Measuring

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The Importance Of Learning Analytics In Instructional Design - eLearning Industry

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Every time a student interacts with your Learning Management System, another piece of data is created and collected. Every login, button click, chat entry, assessment, and time stamp is tracked and recorded. Many Instructional Designers don't take full advantage of this data-but with learning analytics (LA), you can use that data in powerful ways to impact not only your course design, but much more.

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Measuring Training Using Analytics Article 

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Measuring Training Using Analytics Article 

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How To Measure Training Using Learning Analytics

Learning and Development professionals are frequently asked to report on the effectiveness of their training programs. However, reporting simple completion statistics for training just isn't cutting it anymore. Measuring and reporting the return on investment (ROI) for training is essential. Without being able to measure training properly, though, this is a very difficult challenge. Modern learning analytics provide the measurements that allow training directors to examine how effective their training is at achieving their business goals.

Mobile training applications such as Practi can measure and report complex learning behavior that paints a much fuller picture of training results and the business impact of learning.

Being able to measure things like learner engagement and levels of expertise acquisition can help businesses make better use of training data.

It is no longer sufficient to report that 85% of your team completed a $15,000 eLearning program. Increasingly, directors of learning are being asked to report on the ROI for their training by answering questions like:

How did the training help to achieve business objectives?

What are the long term positive business impacts of the training?

How will the training directly enhance team performance?

To answer these questions, training directors and learning management professionals need to make use of deeper learning analytics provided by modern and mobile Learning Management Systems.

Engaged learners are often your indicator of training success. But what is engagement and how do you measure and report this using learning analytics?

Mobile learning applications, such as Practi, can measure things like initial training engagement factors which report on:

Which learners sign in and begin their learning quickly.

Which areas of your training content do learners engage with the most initially.

Which group of learners starts actively training (as opposed to signing in and out, abandoning unfinished material, etc).

How many learners access optional material and in which sequence.

Engagement Measures Are Meaningful

When training managers are able to use real time learning data and mobile learning analytics to measure things like engagement, they can identify things like:

Who is actively on a path toward learning.

Who might need a reminder or some coaching.

Will the team reach their training goals within a time frame.

The amount of data collected by mobile learning applications such as Practi allows for some predictive analytics that can report on such this as:

1. Likely To Succeed.

Learners who sign in, start and complete material, independently work in blocks of twenty minutes or more, quickly correct their mistakes, and perform other learning behaviors that indicate learning success, are those who can be identified early as "likely to succeed".

Why measure this? When you identify these learners early in their training, you can provide positive feedback and coaching that will ensure their success. Early training intervention that encourages success is one of the greatest factors in building a culture of continuous learning and improvement.

2. Needs Coaching.

Learners who sign in and out without attempting or completing material, or who abandon material or skip around in training content without moving sequentially, or who become "stuck" in a topic area, or other metrics that indicate a learning block, can benefit greatly from some coaching.

Why measure this? When we help struggling learners by intervening with coaching, we support a growth mindset for the learner and build that mindset within the learning culture. Quick and early intervention is also a part of the most important stage in any learning system which is feedback. Intervening with struggling learners means you can quickly discover whether content needs updating, whether there are technical problems unrelated to learning, whether a learner has a language barrier or other challenges.

3. On The Path To Competency.

Learners who move through material deliberately, showing measures of focus, fixing mistakes, accessing and reading feedback, can be identified early as those likely to attain competency.

Why measure this? Again, the opportunity to provide learners with feedback that reinforces their deliberate learning behaviors helps to coach them to ongoing success. There is strong evidence that learners who engage in metacognition - "learning to learn" is one of these - develop quickly into successful independent learners.

Making The Best Of Modern Learning Data And Analytics

New Learning Management Systems that are built for "mobile first" training are able to collect and report on a richer range of learning data. This data can even be pushed back to the learner to support and encourage them. For example, successful learning incorporates the 3 Fs: Focus (the learning process), Feedback (use of learning data), Fix it (learner's continuous improvement). Learning data can deliver feedback to the learner which is customized to reflect both the learner's past behavior and can recommend future actions to improve success.

Mobile training apps such as Practi offer access to more and deeper learning analytics which means that training directors don't have to wait until the end of a course to discover if their team is disengaged or successful. By using learning analytics, such as those provided by Practi, learning managers can measure training engagement and receive the data they require to ensure that their whole team can succeed.

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Learning Analytics: Why It's Important To Measure Training

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Learning and Development professionals are frequently asked to report on the effectiveness of their training programs. However, reporting simple completion statistics for training just isn't cutting it anymore. Measuring and reporting the return on investment (ROI) for training is essential. Without being able to measure training properly, though, this is a very difficult challenge.

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Barneveld, A., Arnold, K.E., & Campbell, J. P. (2012). Analytics in higher education: Establishing a common language. Retrieved from
https://library.educause.edu/resources/2012/1/analytics-in-higher-education-establishing-a-common-language

Long, P., & Siemens, G. (2011). Penetrainting the fog: Analytics in Learning and Education. Retrieved from https://er.educause.edu/articles/2011/9/penetrating-the-fog-analytics-in-learning-and-education

Pearson Assessment. (2018). Own your learning with Schoolnet. Retrieved from https://www.pearsonassessments.com/largescaleassessment/products-services/schoolnet.html