Difference between revisions of "Algorithmic Bias in Education"
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== Algorithmic Bias in Education == | == Empirical Evidence for Algorithmic Bias in Education: The Wiki == | ||
This Wiki summarizes the current evidence surrounding Algorithmic Bias in Education: | This Wiki summarizes the current peer-reviewed published evidence surrounding Algorithmic Bias in Education: | ||
which groups are impacted, and in which contexts. | which groups are impacted, and in which contexts. | ||
| Line 7: | Line 7: | ||
Baker, R.S., Hawn, M.A. (in press) Algorithmic Bias in Education. To appear in <em>International Journal of Artificial Intelligence and Education</em> | Baker, R.S., Hawn, M.A. (in press) Algorithmic Bias in Education. To appear in <em>International Journal of Artificial Intelligence and Education</em> | ||
([https://www.upenn.edu/learninganalytics/ryanbaker/AlgorithmicBiasInEducation_rsb3.7.pdf pdf]) | ([https://www.upenn.edu/learninganalytics/ryanbaker/AlgorithmicBiasInEducation_rsb3.7.pdf pdf]) | ||
Note: Within this Wiki, we recommend that page editors use the group labels originally | |||
used within the publications being cited, to best represent the articles included here. We also request that each page center the members of the group the page is about. | |||
This wiki can be cited as | |||
Penn Center for Learning Analytics (*current year*) Empirical Evidence for Algorithmic Bias in Education: The Wiki. | |||
Philadelphia, PA: Penn Center for Learning Analytics. | |||
Retrieved *current date* from https://www.pcla.wiki/index.php/Algorithmic_Bias_in_Education | |||
== By Group Impacted == | == By Group Impacted == | ||
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* [[Gender: Non-Binary and Transgender Learners]] | * [[Gender: Non-Binary and Transgender Learners]] | ||
* [[Sexual Orientation]] | * [[Sexual Orientation]] | ||
* [[National Origin or National Location]] | * [[National Origin or National Location]] | ||
* [[International Students]] | * [[International Students]] | ||
| Line 31: | Line 38: | ||
* [[Children of Migrant Workers]] | * [[Children of Migrant Workers]] | ||
* [[Religion and Religious Background]] | * [[Religion and Religious Background]] | ||
* [[Public or Private K-12 School]] | |||
* [[Intersectional Research]] | * [[Intersectional Research]] | ||
| Line 36: | Line 44: | ||
* [[At-risk/Dropout/Stopout/Graduation Prediction]] | * [[At-risk/Dropout/Stopout/Graduation Prediction]] | ||
* [[Course Grade and GPA Prediction]] | * [[Course Grade and GPA Prediction]] | ||
*National and International Examination | *[[National and International Examination]] | ||
* [[Short-term Performance and Learning Gains Prediction]] | * [[Short-term Performance and Learning Gains Prediction]] | ||
* [[Automated Essay Scoring]] | * [[Automated Essay Scoring]] | ||
| Line 43: | Line 51: | ||
* [[Student Knowledge Modeling]] | * [[Student Knowledge Modeling]] | ||
* [[Engagement and Affect Detection]] | * [[Engagement and Affect Detection]] | ||
*[[Self-regulated Learning]] | |||
* [[Task/Activity Quit Prediction]] | |||
* [[Social Network Link Prediction]] | |||
Latest revision as of 14:59, 15 February 2023
Empirical Evidence for Algorithmic Bias in Education: The Wiki
This Wiki summarizes the current peer-reviewed published evidence surrounding Algorithmic Bias in Education: which groups are impacted, and in which contexts.
For a relatively recent review on this topic, see Baker, R.S., Hawn, M.A. (in press) Algorithmic Bias in Education. To appear in International Journal of Artificial Intelligence and Education (pdf)
Note: Within this Wiki, we recommend that page editors use the group labels originally used within the publications being cited, to best represent the articles included here. We also request that each page center the members of the group the page is about.
This wiki can be cited as Penn Center for Learning Analytics (*current year*) Empirical Evidence for Algorithmic Bias in Education: The Wiki. Philadelphia, PA: Penn Center for Learning Analytics. Retrieved *current date* from https://www.pcla.wiki/index.php/Algorithmic_Bias_in_Education
By Group Impacted
- Race and Ethnicity
- Gender: Male/Female
- Gender: Non-Binary and Transgender Learners
- Sexual Orientation
- National Origin or National Location
- International Students
- Native Language and Dialect
- Learners with Disabilities
- Age
- Urbanicity
- Parental Educational Background
- Socioeconomic Status
- Military-Connected Status
- Children of Migrant Workers
- Religion and Religious Background
- Public or Private K-12 School
- Intersectional Research
By Algorithm Application
- At-risk/Dropout/Stopout/Graduation Prediction
- Course Grade and GPA Prediction
- National and International Examination
- Short-term Performance and Learning Gains Prediction
- Automated Essay Scoring
- Speech Recognition for Education
- Other NLP Applications of Algorithms in Education
- Student Knowledge Modeling
- Engagement and Affect Detection
- Self-regulated Learning
- Task/Activity Quit Prediction
- Social Network Link Prediction