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Gist of LAK 22 paper

Competency 7.4: Describe how models might be used in Learning Analytics research, specifically for the problem of assessing some reasons for attrition along the way in MOOCs. One particular model described by Dr. Carolyn talks about how certain properties of discussion correlate to dropout in MOOC. It explores how analyses of sentiment predict attrition over time ...

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 ...

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 ...

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 ...

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: 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 ...

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: 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: 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: 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 ...