- Questioning Learning Analytics – Cultivating critical engagement (LAK’22)
Gist of LAK 22 paper
- Competency 7.3/ Assignment
Building a simple text classification experiment – Training and evaluating a simple predictive model
I used LightSIDE tool as explained by Dr. Carolyn to run a simple classification experiment. The tool is easy to use and straightforward if we follow the steps.
In the Extract Features pane, I loaded the NewsgroupTopic dataset from the sample data directory ...
- Competency 7.1/ 7.2 Text Mining
Text Mining is the process of extracting and identifying useful and meaningful information, from different sources of unstructured text data.
Prominent Areas of Text Mining
Information Retrieval:
Information Retrieval is the process of searching and retrieving the required document from a collection of documents based on the given search query. The search engines we use like Google, Yahoo ...
- Competency 6.2: Key Diagnostic Metrics
A part of Week 6 was designed to learn about the diagnostic metrics, to see how well our model does, as either classifiers or regressors.
Metrics for Classifiers
Accuracy:
The easiest measure of model goodness is accuracy. It is also called agreement, when measuring the inter-rater reliability.Accuracy = # of agreements/ Total # of assessmentsIt is generally not ...
- Competency 6.1: Engineer both feature and training labels
My notes/ learning
Behavior Detectors
Behavior detectors are automated (predictive) models that can infer from log files whether a student is behaving in a certain way.
Behaviors:
Disengaged behaviors
-gaming the system by trying to succeed without learning
-off-task behavior
-carelessness by giving wrong answer even when having the required skills
-WTF behavior – Without Thinking Fastidiously (by doing unrelated tasks while using ...
- Competency 5.1/ Week 5 Activity
Competency 5.1: Learn to conduct prediction modeling effectively and appropriately.
I think this competency can be achieved if we are able to complete the given activity in RapidMiner. It is quite difficult for a newbie, but its well-described in the course and definitely doable 🙂
We were asked to build a set of detectors predicting the variable ONTASK for ...
- Competency 5.2/ Week 5 Reflection
A quick intro – I skipped weeks 3 & 4 for the time being since I was very much behind schedule coz of starting late. I jumped to Week 5 – Prediction modeling so that I can participate in the discussion and bazaar but sadly I was still lagging to participate. I’m aiming to complete ...
- Competency 2.3
Competency 2.3: Evaluate the impact of policy and strategic planning on systems-level deployment of learning analytics.
#Assignment 68
Learning analytics could create a bigger impact on learning if implemented top-down than bottom up due to the availability of big data.However, the deployment of learning analytics faces many challenges at the institutional level:
1. Acceptance:To work big on big ...
- Competency 2.2
Competency 2.2: Download, install, and conduct basic analytics using Tableau software.
For the purpose of this competency, I’ve used a sample excel sheet with simple sales data. I’ve installed Tableau for this exercise and used a two sheet excel. My sample data below:
I’ve then added rows and columns to create visualizations. Common tools from the Show ...
- Competency 2.1
Competency 2.1: Describe the learning analytics data cycle.
Learning Analytics Data Cycle
The process of Learning Analytics is a cycle and not linear due to the fact that we need to revisit the steps according to the data and results.
I see the data cycle as follows:
Cleaning the data could be time consuming and challenging ...
- Competency 1.2
Competency 1.2: Define learning analytics and detail types of insight they can provide to educators and learners.My definition of Learning Analytics (based on previous definitions and my understanding):Learning Analytics is something which will help us to process simple data into useful information using different methods. A lot of minute, but useful information may be lost in ...