Research on Intelligent Tutoring Systems
Budget: $50 – $100 USD
This project is to write a research paper of intelligent tutoring system approaches for predicting student performance. The review must consist of 15 unique and varied techniques from unique peer-reviewed published papers between 2015-2022. The focus is on 15 techniques to calculate student performance prediction (probability if a student will get a question correct).
The paper that you will write (font times new roman, single spaced, 11pt font) will contain the following for each of the 15 prediction techniques you find. Each of the following bullets should be 1-2 sentences for each prediction technique in your own words (no copying from text/plagiarism):
* Name of the technique and overall description of how it works.
* The type of the prediction: Is it Markov inference-based, Bayesian, logistic regression, neural network, probabilistic, etc. ?
* What metrics does the technique use as input and what does it output?
* What discipline is this prediction technique used for? For example, Elementary school math, college algebra, science, literature, etc.
* What techniques are compared to this new prediction technique and what were the general experiment results (did this technique improve prediction accuracy compared to an older technique? If so or not, by how much?
* What did they authors conclude to be the reason for the results?)
* How did the technique evaluate itself to older techniques in the experiments?
* What are the advantages of this prediction technique?
* What are the disadvantages of the technique
* Provide the full citation reference (must be from 2015 to 2022)
* Provide the pdf of the paper
The paper that you will write (font times new roman, single spaced, 11pt font) will contain the following for each of the 15 prediction techniques you find. Each of the following bullets should be 1-2 sentences for each prediction technique in your own words (no copying from text/plagiarism):
* Name of the technique and overall description of how it works.
* The type of the prediction: Is it Markov inference-based, Bayesian, logistic regression, neural network, probabilistic, etc. ?
* What metrics does the technique use as input and what does it output?
* What discipline is this prediction technique used for? For example, Elementary school math, college algebra, science, literature, etc.
* What techniques are compared to this new prediction technique and what were the general experiment results (did this technique improve prediction accuracy compared to an older technique? If so or not, by how much?
* What did they authors conclude to be the reason for the results?)
* How did the technique evaluate itself to older techniques in the experiments?
* What are the advantages of this prediction technique?
* What are the disadvantages of the technique
* Provide the full citation reference (must be from 2015 to 2022)
* Provide the pdf of the paper