THE KNOWLEDGE WE WEAVE

  • WORK THAT INSPIRES US:

    Blume, A. K., Tehee, M., & Galliher, R. V. (2019). Experiences of discrimination and prejudice among American Indian youth: Links to psychosocial functioning. In H. Fitzgerald H., D. Johnson, D. Qin, F. Villarruel, & J. Norder (Eds.) Handbook of children and prejudice, (pp. 389-404). Springer. https://doi.org/10.1007/978-3-030-12228-7_22

    Costanza-Chock, S. (2020). Design justice: Community-led practices to build the worlds we need. The MIT Press.

    Erikson, E. H. (1994). Identity: Youth and Crisis. W. W. Norton & Company.

    Goins, R. T., Garroutte, E. M., Fox, S. L., Geiger, S. D., & Manson, S. M. (2011). Theory and practice in participatory research: Lessons from the Native elder care study. The Gerontologist, 51(3), 285–294. https://doi.org/10.1093/geront/gnq130

    Greco, L. A., Lambert, W., & Baer, R. A. (2008). Psychological inflexibility in childhood and adolescence: Development and evaluation of the Avoidance and Fusion Questionnaire for Youth. Psychological Assessment, 20(2), 93–102. https://doi.org/10.1037/1040-3590.20.2.93

    Hodge, F. S., & Nandy, K. (2011). Predictors of Wellness and American Indians. Journal of Health Care for the Poor and Underserved, 22(3), 791–803. https://doi.org/10.1353/hpu.2011.0093

    Israel, B. A., Schulz, A. J., Parker, E. A., & Becker, A. B. (1998). Review of community-based research: Assessing partnership approaches to improve public health. Annual Review of Public Health, 19, 173–202. https://doi.org/10.1146/annurev.publhealth.19.1.173

    Jones, M. D., & Galliher, R. V. (2007). Ethnic Identity and Psychosocial Functioning in Navajo Adolescents. Journal of Research on Adolescence, 17(4), 683–696.

    King, L., Gubele, R., & Anderson, J. R. (2015). Survivance, Sovereignty, and Story: Teaching American Indian Rhetorics. University Press of Colorado.

    Koithan, M., & Farrell, C. (2010). Indigenous Native American Healing Traditions. The Journal for Nurse Practitioners, 6(6), 477–478. https://doi.org/10.1016/j.nurpra.2010.03.016

    Lyons, S. R. (2000). Rhetorical Sovereignty: What Do American Indians Want from Writing? College Composition and Communication, 51(3), 447–468. https://doi.org/10.2307/358744

    Mohatt, N. V., Thompson, A. B., Thai, N. D., & Tebes, J. K. (2014). Historical trauma as public narrative: A conceptual review of how history impacts present-day health. Social Science & Medicine, 106, 128–136. https://doi.org/10.1016/j.socscimed.2014.01.043

    Narvaez, D., & Hill, P. L. (2010). The relation of multicultural experiences to moral judgment and mindsets. Journal of Diversity in Higher Education, 3(1), 43–55. https://doi.org/10.1037/a0018780

    National Association of Social Workers. (2015). Standards and indicators for cultural competence in social work practice. https://www.socialworkers.org/LinkClick.aspx?fileticket=PonPTDEBrn4%3D&portalid=0

    Phinney, J. S. (1992). The Multigroup Ethnic Identity Measure A New Scale for Use with Diverse Groups. Journal of Adolescent Research, 7(2), 156–176. https://doi.org/10.1177/074355489272003

    Ryoo, J. and Shea, M. (2015). Activity: Mapping shared goals and outcomes in a partnership. http://researchandpractice.org/resource/value-mapping

    Spencer, M. B., Swanson, D. P., & Cunningham, M. (1991). Ethnicity, ethnic identity, and competence formation: Adolescent transition and cultural transformation. The Journal of Negro Education, 60(3), 366–387. https://doi.org/10.2307/2295490

    Swinomish Tribal Mental Health Project. (2002). A Gathering of wisdoms. Tribal mental health: A cultural perspective. Swinomish Tribal Community.

    Tehee, M., Isaacs, D., & Domenech Rodríguez, M. M. (2020). The elusive construct of cultural competence. In L. T. Benuto, F. R. Gonzalez, & J. Singer (Eds.), Handbook of Cultural Factors in Behavioral Health (pp. 11–24). Springer International Publishing. https://doi.org/10.1007/978-3-030-32229-8_2

    Vizenor, G. (2008). Survivance: Narratives of Native Presence. U of Nebraska Press.

    Wang, Y.-W., Davidson, M. M., Yakushko, O54. F., Savoy, H. B., Tan, J. A., & Bleier, J. K. (2003). The Scale of Ethnocultural Empathy: Development, validation, and reliability. Journal of Counseling Psychology, 50(2), 221–234. https://doi.org/10.1037/0022-0167.50.2.221

    Winter, J., & Boudreau, J. (2018). Supporting self-determined indigenous innovations: Rethinking the digital divide in Canada. Technology Innovation Management Review, 8(2).

  • WORK THAT INSPIRES US:

    Agre, P. E. (1997b). Toward a Critical Technical Practice: Lessons Learned in Trying to Reform AI. In G. C. Bowker, S. L. Star, W. Turner, & L. Gasser (Eds.), Social Science, Technical Systems and Cooperative Work: Beyond the Great Divide. Erlbaum.

    Ammanabrolu, P., Tien, E., Cheung, W., Luo, Z., Ma, W., Martin, L., & Riedl, M. (2019). Guided neural language generation for automated storytelling. Proceedings of the Second Workshop on Storytelling, 46–55.

    Bae, B.-C., & Young, R. M. (2009). Suspense? Surprise! or How to Generate Stories with Surprise Endings by Exploiting the Disparity of Knowledge between a Story’s Reader and its Characters. Proceedings 2nd International Conference on Interactive Digital Storytelling, 304–307.

    Cardona-Rivera, R. E. (2020). Foundations of a Computational Science of Game Design: Abstractions and Tradeoffs. Proceedings of the 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 167–174.

    Chambers, N. & Jurafsky, D. (2008). Unsupervised Learning of Narrative Event Chains. In Proceedings of the Annual Meeting of the Association for Computational Linguistics, 789–797.

    Corbett, J. M. R. (2018). Indigenizing computer programming for cultural maintenance. Conference Companion of the 2nd International Conference on Art, Science, and Engineering of Programming, 243–244.

    Corbett, J., & Kulchyski, T. (2009). Anti social-computing: Indigenous language, digital video and intellectual property. Participatory Learning and Action, 59(1), 52–58.

    Davis, R., Shrobe, H., & Szolovits, P. (1993). What is a knowledge representation? AI Magazine, 14(1), 17–33.

    Eubanks, V. (2018). Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. St. Martin’s Publishing Group.

    Gervas, P. (2009). Computational Approaches to Storytelling and Creativity. AI Magazine, 30(3), 49–49.

    Guan, J., Wang, Y., & Huang, M. (2019). Story ending generation with incremental encoding and commonsense knowledge. Proceedings of the 33rd AAAI Conference on Artificial Intelligence, 6473–6480.

    Guzdial, M., Liao, N., Chen, J., Chen, S.-Y., Shah, S., Shah, V., Reno, J., Smith, G., & Riedl, M. O. (2019). Friend, collaborator, student, manager: How design of an ai-driven game level editor affects creators. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1–13.

    Ito, J. (2017). Resisting reduction: A manifesto. Journal of Design and Science. https://doi.org/10.21428/8f7503e4

    Jiang, T., & Riloff, E. (2018). Learning Prototypical Goal Activities for Locations. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 1297–1307.

    Kim, K.-M., Heo, M.-O., Choi, S.-H., & Zhang, B.-T. (2017). DeepStory: Video Story QA by Deep Embedded Memory Networks. arXiv Preprint arXiv:1707. 00836.

    Kling, R., Star, S. L., Kiesler, S., Agre, P., Bowker, G., Attewell, P., & Ntuen, C. (1998). Human Centered Systems in the Perspective of Organizational and Social Informatics (T. Huang & J. Flanigan (eds.); No. WP-97-04; Vol. 28, pp. 22–29). National Science Foundation.

    Kybartas, B., & Bidarra, R. (2016). A survey on story generation techniques for authoring computational narratives. IEEE Transactions on Computational Intelligence in AI and Games, 9(3), 239–253.

    Lewis, J. E., Arista, N., Pechawis, A., & Kite, S. (2018). Making Kin with the Machines. Journal of Design and Science. https://doi.org/10.21428/bfafd97b

    Li, B., Lee-Urban, S., Appling, D. S., & Riedl, M. O. (2012). Crowdsourcing Narrative Intelligence. Advances in Cognitive Systems, 1, 1–18.

    Litts, B. K., Searle, K. A., Brayboy, B. M. J., & Kafai, Y. B. (2020). Computing for all?: Examining critical biases in computational tools for learning. British Journal of Educational Technology. https://doi.org/10.1111/bjet.13059

    Martens, C., & Smith, G. (2020). Towards a Critical Technical Practice of Narrative Intelligence. Proceedings of the 12th Intelligent Narrative Technologies Workshop at the 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment.

    McCarthy, J. (1990). An example for natural language understanding and the AI problems it raises. Formalizing Common Sense: Papers by John McCarthy, 355.

    Mitchell, M., Baker, D., Moorosi, N., Denton, E., Hutchinson, B., Hanna, A., Gebru, T., & Morgenstern, J. (2020). Diversity and Inclusion Metrics in Subset Selection. In Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 117–123.

    Mostafazadeh, N., Chambers, N., He, X., Parikh, D., Batra, D., Vanderwende, L., Kohli, P., & Allen, J. (2016). A corpus and cloze evaluation for deeper understanding of commonsense stories. Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 839–849.

    Mueller, E. T. (2000). Prospects for in-depth story understanding by computer. arXiv Preprint arXiv:0003003.

    Mueller, E. T. (2013). Computational Models of Narrative. Sprache Und Datenverarbeitung (SDV): International Journal of Language Processing, Special Issue on Formal and Computational Models of Narrative, 37, 11–39.

    Noble, S. U. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press.

    O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown.

    Parvin, N. (2018). Doing Justice to Stories: On Ethics and Politics of Digital Storytelling. Engaging Science, Technology, and Society, 4(0), 515–534.

    Pohawapatchoko, C. C., Jr. (2018). Cultural Constructionism: An Indigenous Computing Experience (C. H. Lewis (ed.)) [Doctor of Philosophy]. University of Colorado, Boulder.

    Qin, L., Bosselut, A., Holtzman, A., Bhagavatula, C., Clark, E., & Choi, Y. (2019). Counterfactual Story Reasoning and Generation. In arXiv [cs.CL]. arXiv. http://arxiv.org/abs/1909.04076

    Ribeiro, M. T., Singh, S., & Guestrin, C. (2016). “Why should I trust you?” Explaining the predictions of any classifier. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1135–1144.

    Riedl, M. O. (2016). Computational narrative intelligence: A human-centered goal for artificial intelligence. arXiv Preprint arXiv:1602. 06484.

    Roemmele, M., Bejan, C. A., & Gordon, A. S. (2011). Choice of plausible alternatives: An evaluation of commonsense causal reasoning. Proceedings of the 2011 AAAI Spring Symposium Series.

    Rüde, U., Willcox, K., McInnes, L. C., & Sterck, H. D. (2018). Research and Education in Computational Science and Engineering. SIAM Review, 60(3), 707–754.

    Ruef, J. L., Johnson, S. R., Jacob, M. M., Jansen, J., & Beavert, V. (2020). Why STEM Needs Indigenous Traditional Ecological Knowledge: A Case Study of Ichishkíin Math. International Journal of Gender, Science and Technology, 11(3), 429–4.

    Schank, R. C. (1995). Tell me a story: Narrative and intelligence. Northwestern University Press.

    Turkle, S. (2005). The Second Self, Twentieth Anniversary Edition: Computers and the Human Spirit. MIT Press.

    Winston, P. H. (2011). The Strong Story Hypothesis and the Directed Perception Hypothesis. Proceedings of the AAAI Fall Symposium on Advances in Cognitive Systems, 345–352.

    Yao, L., Peng, N., Weischedel, R., Knight, K., Zhao, D., & Yan, R. (2019). Plan-and-write: Towards better automatic storytelling. Proceedings of the 33rd AAAI Conference on Artificial Intelligence, 7378–7385.

    Young, R. M. (1999). Notes on the use of plan structures in the creation of interactive plot. Proceedings of the AAAI Fall Symposium on Narrative Intelligence, 164–167.

  • WORK THAT INSPIRES US:

    Castagno, A. E., & Brayboy, B. M. J. (2008). Culturally Responsive Schooling for Indigenous Youth: A Review of the Literature. In Review of Educational Research 78(4) 941–993.

    Covarrubias, R., & Fryberg, S. A. (2015). The impact of self-relevant representations on school belonging for Native American students. Cultural Diversity & Ethnic Minority Psychology, 21(1), 10–18.

    Fryberg, S. A., & Eason, A. E. (2017). Making the Invisible Visible: Acts of Commission and Omission. Current Directions in Psychological Science, 26(6), 554–559.

    Gay, G. (2018). Culturally responsive teaching: Theory, research, and Practice. Teachers College Press.

    Journell, W. (2009). Setting Out the (Un) Welcome Mat: A Portrayal of Immigration in State Standards for American History. In The Social Studies 100(4), 160–168.

    Ladson-Billings, G. (1995). Toward a Theory of Culturally Relevant Pedagogy. American Educational Research Journal, 32(3), 465–491. https://doi.org/10.3102/00028312032003465

    Leigh-Osroosh, K. T., & Hutchison, B. (2019). Cultural Identity Silencing of Native Americans in Education. Race and Pedagogy Journal: Teaching and Learning for Justice, 4(1), 3.

    Litts, B. K., Tehee, M., Jenkins, J., Baggaley, S., Isaacs, D., Hamilton, M. M., & Yan, L. (2020). Culturally disruptive research: A critical (re)engagement with research processes and teaching practices. Information and Learning Sciences, 121(9/10), 769–784. https://doi.org/10.1108/ILS-02-2020-0019

    Litts, B.K., Tehee, M., Justis, N., Yan, L., Baggaley, S., & Jenkins, J. (2020, November). Debating the Bears Ears: Employing Culturally Disruptive Pedagogy for Curriculum Redesign. Association for Educational Communications & Technology Annual Conference.

    McCarty, T., & Lee, T. (2014). Critical culturally sustaining/revitalizing pedagogy and Indigenous education sovereignty. Harvard Educational Review, 84(1), 101–124.

    National Congress of American Indians. (2019). Becoming Visible: A Landscape Analysis of State Efforts to Provide Native American Education for All. Washington, DC.

    Paris, D. (2012). Culturally Sustaining Pedagogy: A Needed Change in Stance, Terminology, and Practice. Educational Researcher , 41(3), 93–97.

    Paris, D., & Samy Alim, H. (2017). Culturally Sustaining Pedagogies: Teaching and Learning for Justice in a Changing World. Teachers College Press.

    San Pedro, T. (2018). Abby as Ally: An Argument for Culturally Disruptive Pedagogy. American Educational Research Journal, 55(6), 1193–1232.

    Shear, S. B., Knowles, R. T., Soden, G. J., & Castro, A. J. (2015). Manifesting destiny: Re/presentations of indigenous peoples in K--12 US history standards. Theory & Research in Social Education, 43(1), 68–101.

    Spencer, M. B. (1999). Social and cultural influences on school adjustment: The application of an identity-focused cultural ecological perspective. Educational Psychologist, 34(1), 43–57. https://doi.org/10.1207/s15326985ep3401_4

OUR GOALS AND VALUES

Our ultimate goal is to invent Tribally-created computational design experience prototypes that preserve Indigenous history, represent Indigenous communities’ ways of being and knowing, and can be effectively shared in K-12 classrooms. We intend for this project to empower Tribal members to (re)engage technologies that have historically created and perpetuated disparities that have caused significant harm to their communities. 

The lack of representation of Indigenous issues and perspectives in K-12 education curricula in the United States has led to numerous negative consequences for Indigenous students and is a disservice to all students. While technology has the potential to support teachers and Indigenous Knowledge Holders in addressing this issue, very little work has been done on Indigenous representation within the context of narrative technologies. We argue that these technologies perpetuate systemic racism and potentially cause further harm and disenfranchisement for Indigenous communities. As such, our proposed project aims to examine and reformulate the underlying computational models of these technologies to fundamentally decolonize the process of creating them, making them more inclusive and respectful of Indigenous ways of being and knowing.