Currently browsing: Items authored or edited by Tina Papathoma

14 items in this list.
Generated on Tue Dec 7 05:25:58 2021 GMT.

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Robinson, L.D.; Miller, A.E.; Burton, V.J.; Herodotou, Christothea; Higgins, L.; Miller, G.R.M.; Young, A.N.; Ghadiri Khanaposhtani, M.; Benavides Lahnstein,, A.I.; Sanghera, H.K.; Johnson, R.F.; Aristeidou, Maria; Ballard, H.L.; Jennewein, J.; Lorke, J.; Pratt-Taweh, S.; Wardlaw, J.; Ismail, Nashwa; Pauly, G.B.; Papathoma, Tina and Swanson, R.D. (2021). Enhancing youth learning through Community and Citizen Science: a guide for practitioners. Natural History Museum, London.

Papathoma, Tina; Ferguson, Rebecca and Vogiatzis, Dimitrios (2021). Accessible learning, accessible analytics: a virtual evidence café. In: Companion Proceedings 11th International Conference on Learning Analytics & Knowledge (LAK21).

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Herodotou, Christothea; Papathoma, Tina; Aristeidou, Maria; Miller, Grant; Ghadiri, Maryam; Lorke, Julia and Ballard, Heidi (2020). What do young volunteers learn from participation in online crowdsourced citizen science? Environmental science learning through Zooniverse. In: ECSA conference 2020, 7-10 Sep 2020, Trieste, Italy.

Scanlon, Eileen and Papathoma, Tina (2020). Citizen science as interdisciplinary working. In: Networked Learning Conference, 2020, 18-20 May 2020, Kolding, Denmark.

Papathoma, Tina; Ferguson, Rebecca; Iniesto, Francisco; Rets, Irina; Vogiatzis, Dimitrios and Murphy, Victoria (2020). Guidance on how Learning at Scale can be made more accessible. In: Proceedings of the Seventh ACM Conference on Learning@ Scale, Aug 12-14, Georgia Tech, Atlanta, GA, pp. 289–292.

Hlosta, Martin; Papathoma, Tina and Herodotou, Christothea (2020). Explaining Errors in Predictions of At-Risk Students in Distance Learning Education. In: Artificial Intelligence in Education, Lecture Notes in Computer Science (LNCS), Springer, pp. 119–123.

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Papathoma, Tina; Ferguson, Rebecca; Littlejohn, Allison and Coe, Angela (2016). Making the Production of Learning at Scale more Open and Flexible. In: L@S '16: Proceedings of the Third ACM Conference on Learning @ Scale, ACM, pp. 273–276.

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