Towards Breaking the Learning System Wall Using Multimodal Tutoring Transcriptions

Danielle R Thomas; Marie Cynthia Abijuru Kamikazi; Ashish Gurung; Ishan Miglani; Shivang Gupta; Zachary Levonian; Conrad Borchers; Kenneth R Koedinger

Towards Breaking the Learning System Wall Using Multimodal Tutoring Transcriptions

Danielle R Thomas, Marie Cynthia Abijuru Kamikazi, Ashish Gurung, Ishan Miglani, Shivang Gupta, Zachary Levonian, Conrad Borchers, Kenneth R Koedinger

Correct Metadata for

Use this form to create a GitHub issue with structured data describing the correction. You will need a GitHub account. Once you create that issue, the correction will be reviewed by a staff member.

⚠️ Mobile Users: Submitting this form to create a new issue will only work with github.com, not the GitHub Mobile app.

Important: The Anthology treat PDFs as authoritative. Please use this form only to correct data that is out of line with the PDF. See our corrections guidelines if you need to change the PDF.

Title Adjust the title. Retain tags such as <fixed-case>.

Authors Adjust author names and order to match the PDF.

Abstract Correct abstract if needed. Retain XML formatting tags such as <tex-math>. You may use ... for bold, ... for italic, ... for underline, <sc>...</sc> for small-caps, <tt>...<tt> for typewriter text, <url>...</url> for URLs, <a href=...> for hyperlinks, and <par/> for paragraph breaks.

Verification against PDF Ensure that the new title/authors match the snapshot below. (If there is no snapshot or it is too small, consult the PDF.)

Authors concatenated from the text boxes above:

ALL author names match the snapshot above—including middle initials, hyphens, and accents.

Abstract

To address the "learning system wall," we introduce an AI system that converts tutoring screen recordings into unified transcripts of dialogue and on-screen actions. We present a method for aligning and classifying learning processes against MATHia logs, marking an initial step toward generalizable cross-platform learner modeling.

Anthology ID:: 2026.aimecon-main.70
Volume:: Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers
Month:: October
Year:: 2026
Address:: Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States
Editors:: Joshua Wilson, Christopher Ormerod, Magdalen Beiting-Parrish
Venue:: AIME-Con
SIG:
Publisher:: National Council on Measurement in Education (NCME)
Note:
Pages:: 622–630
Language:
URL:: https://aclanthology.org/2026.aimecon-main.70/
DOI:
Bibkey:
Cite (ACL):: Danielle R Thomas, Marie Cynthia Abijuru Kamikazi, Ashish Gurung, Ishan Miglani, Shivang Gupta, Zachary Levonian, Conrad Borchers, and Kenneth R Koedinger. 2026. Towards Breaking the Learning System Wall Using Multimodal Tutoring Transcriptions. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 622–630, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):: Towards Breaking the Learning System Wall Using Multimodal Tutoring Transcriptions (Thomas et al., AIME-Con 2026)
Copy Citation:
PDF:: https://aclanthology.org/2026.aimecon-main.70.pdf

PDF Cite Search Fix data

Export citation

BibTeX
MODS XML
Endnote
Preformatted

@inproceedings{thomas-etal-2026-towards,
    title = "Towards Breaking the Learning System Wall Using Multimodal Tutoring Transcriptions",
    author = "Thomas, Danielle R  and
      Abijuru Kamikazi, Marie Cynthia  and
      Gurung, Ashish  and
      Miglani, Ishan  and
      Gupta, Shivang  and
      Levonian, Zachary  and
      Borchers, Conrad  and
      Koedinger, Kenneth R",
    editor = "Wilson, Joshua  and
      Ormerod, Christopher  and
      Beiting-Parrish, Magdalen",
    booktitle = "Proceedings of the Artificial Intelligence in Measurement and Education Conference ({AIME}-Con): Full Papers",
    month = oct,
    year = "2026",
    address = "Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States",
    publisher = "National Council on Measurement in Education (NCME)",
    url = "https://aclanthology.org/2026.aimecon-main.70/",
    pages = "622--630",
    ISBN = "979-8-9983004-0-0",
    abstract = "To address the ``learning system wall,'' we introduce an AI system that converts tutoring screen recordings into unified transcripts of dialogue and on-screen actions. We present a method for aligning and classifying learning processes against MATHia logs, marking an initial step toward generalizable cross-platform learner modeling."
}

Download as File

<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="thomas-etal-2026-towards">
    <titleInfo>
        <title>Towards Breaking the Learning System Wall Using Multimodal Tutoring Transcriptions</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Danielle</namePart>
        <namePart type="given">R</namePart>
        <namePart type="family">Thomas</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Marie</namePart>
        <namePart type="given">Cynthia</namePart>
        <namePart type="family">Abijuru Kamikazi</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Ashish</namePart>
        <namePart type="family">Gurung</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Ishan</namePart>
        <namePart type="family">Miglani</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Shivang</namePart>
        <namePart type="family">Gupta</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Zachary</namePart>
        <namePart type="family">Levonian</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Conrad</namePart>
        <namePart type="family">Borchers</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Kenneth</namePart>
        <namePart type="given">R</namePart>
        <namePart type="family">Koedinger</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2026-10</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Joshua</namePart>
            <namePart type="family">Wilson</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Christopher</namePart>
            <namePart type="family">Ormerod</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Magdalen</namePart>
            <namePart type="family">Beiting-Parrish</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>National Council on Measurement in Education (NCME)</publisher>
            <place>
                <placeTerm type="text">Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
        <identifier type="isbn">979-8-9983004-0-0</identifier>
    </relatedItem>
    <abstract>To address the “learning system wall,” we introduce an AI system that converts tutoring screen recordings into unified transcripts of dialogue and on-screen actions. We present a method for aligning and classifying learning processes against MATHia logs, marking an initial step toward generalizable cross-platform learner modeling.</abstract>
    <identifier type="citekey">thomas-etal-2026-towards</identifier>
    <location>
        <url>https://aclanthology.org/2026.aimecon-main.70/</url>
    </location>
    <part>
        <date>2026-10</date>
        <extent unit="page">
            <start>622</start>
            <end>630</end>
        </extent>
    </part>
</mods>
</modsCollection>

Download as File

%0 Conference Proceedings
%T Towards Breaking the Learning System Wall Using Multimodal Tutoring Transcriptions
%A Thomas, Danielle R.
%A Abijuru Kamikazi, Marie Cynthia
%A Gurung, Ashish
%A Miglani, Ishan
%A Gupta, Shivang
%A Levonian, Zachary
%A Borchers, Conrad
%A Koedinger, Kenneth R.
%Y Wilson, Joshua
%Y Ormerod, Christopher
%Y Beiting-Parrish, Magdalen
%S Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers
%D 2026
%8 October
%I National Council on Measurement in Education (NCME)
%C Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States
%@ 979-8-9983004-0-0
%F thomas-etal-2026-towards
%X To address the “learning system wall,” we introduce an AI system that converts tutoring screen recordings into unified transcripts of dialogue and on-screen actions. We present a method for aligning and classifying learning processes against MATHia logs, marking an initial step toward generalizable cross-platform learner modeling.
%U https://aclanthology.org/2026.aimecon-main.70/
%P 622-630

Download as File

Markdown (Informal)

[Towards Breaking the Learning System Wall Using Multimodal Tutoring Transcriptions](https://aclanthology.org/2026.aimecon-main.70/) (Thomas et al., AIME-Con 2026)

Towards Breaking the Learning System Wall Using Multimodal Tutoring Transcriptions (Thomas et al., AIME-Con 2026)

ACL

Danielle R Thomas, Marie Cynthia Abijuru Kamikazi, Ashish Gurung, Ishan Miglani, Shivang Gupta, Zachary Levonian, Conrad Borchers, and Kenneth R Koedinger. 2026. Towards Breaking the Learning System Wall Using Multimodal Tutoring Transcriptions. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 622–630, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).