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{
    "pk": 27947,
    "title": "Analysis of human problems solving drafts: a methodological approach on the example of Rush Hour",
    "subtitle": null,
    "abstract": "Assessing the quality of a learner’s solution for a given task isan essential step in analyzing a learner’s performance. For awell-defined sequential problem, correctness and optimality ofthe solution as well as its length provide first simple and rea-sonable metrics. However, this ignores the fact that there areconceptually different errors that humans make when solving aproblem. This work proposes a rule-based system of error cat-egories which is able to classify conceptually different errorswith respect to their (assumed) motive. The principles the cat-egories are based on are valid for most well-defined sequentialproblems and can hence serve as a valuable tool in the analy-sis of human solutions for such a problem. In this work, theerror category system is adapted to the game Rush Hour. Weuse the category system as a tool for a detailed analysis of 115human solutions of a Rush Hour game. We found that the mostcommon error type is based on a simple solving heuristic, butmainly occurs in the first half of the solution process. Other er-ror types whose occurrence is numerically less dominant, arestill found in the majority of the solutions. However, they oc-cur in very specific game situations. As a first generalizationapproach of the category system, its application on a furtherdataset containing 56 different Rush Hour tasks and more than31, 000 human solutions yield promising results.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "Problem solving; Solution quality; Error analysis; Error categories; Rush hour"
        }
    ],
    "section": "Publication-based-Talks",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/9mk0v4m7",
    "frozenauthors": [
        {
            "first_name": "Mareike",
            "middle_name": "",
            "last_name": "Bockholt",
            "name_suffix": "",
            "institution": "University of Kaiserslautern",
            "department": ""
        },
        {
            "first_name": "Olaf",
            "middle_name": "",
            "last_name": "Peters",
            "name_suffix": "",
            "institution": "Technical University of Dresden",
            "department": ""
        },
        {
            "first_name": "Susanne",
            "middle_name": "",
            "last_name": "Narciss",
            "name_suffix": "",
            "institution": "Technical University of Dresden",
            "department": ""
        },
        {
            "first_name": "Katharina",
            "middle_name": "A",
            "last_name": "Zweig",
            "name_suffix": "",
            "institution": "University of Kaiserslautern",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2018-01-01T13:00:00-05:00",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27947/galley/17585/download/"
        }
    ]
}