{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T07:43:10Z","timestamp":1773042190782,"version":"3.50.1"},"publisher-location":"Cham","reference-count":48,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031426810","type":"print"},{"value":"9783031426827","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,8,28]],"date-time":"2023-08-28T00:00:00Z","timestamp":1693180800000},"content-version":"vor","delay-in-days":239,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Peer feedback has been widely used in computer-supported collaborative learning (CSCL) setting to improve students\u2019 engagement with massive courses. Although the peer feedback process increases students\u2019 self-regulatory practice, metacognition, and academic achievement, instructors need to go through large amounts of feedback text data which is much more time-consuming. To address this challenge, the present study proposes an automated content analysis approach to identify relevant categories in peer feedback based on traditional and sequence-based classifiers using TF-IDF and content-independent features. We use a data set from an extensive course (N = 231 students) in the setting of engineering higher education. In particular, a total of 2,444 peer feedback messages were analyzed. The CRF classification model based on the TF-IDF features achieved the best performance. The results illustrate that the ability to scale up the automatic analysis of peer feedback provides new opportunities for student-improved learning and improved teacher support in higher education at scale.<\/jats:p>","DOI":"10.1007\/978-3-031-42682-7_27","type":"book-chapter","created":{"date-parts":[[2023,8,29]],"date-time":"2023-08-29T15:01:46Z","timestamp":1693321306000},"page":"399-414","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Understanding Peer Feedback Contributions Using Natural Language Processing"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-9815-5923","authenticated-orcid":false,"given":"Mayara Sim\u00f5es de Oliveira","family":"Castro","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3548-9670","authenticated-orcid":false,"given":"Rafael Ferreira","family":"Mello","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5016-5458","authenticated-orcid":false,"given":"Giuseppe","family":"Fiorentino","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8543-3774","authenticated-orcid":false,"given":"Olga","family":"Viberg","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9454-0793","authenticated-orcid":false,"given":"Daniel","family":"Spikol","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7018-6187","authenticated-orcid":false,"given":"Martine","family":"Baars","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9265-1908","authenticated-orcid":false,"given":"Dragan","family":"Ga\u0161evi\u0107","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,8,28]]},"reference":[{"key":"27_CR1","doi-asserted-by":"publisher","unstructured":"Aggarwal, C.C., Zhai, C.: A survey of text classification algorithms. In: Aggarwal, C., Zhai, C. (eds), Mining Text Data. Springer, Boston, MA (2012). https:\/\/doi.org\/10.1007\/978-1-4614-3223-4_6","DOI":"10.1007\/978-1-4614-3223-4_6"},{"key":"27_CR2","unstructured":"Allahyari, M., et al.: A brief survey of text mining: Classification, clustering and extraction techniques. arXiv preprint arXiv:1707.02919 (2017)"},{"issue":"6","key":"27_CR3","doi-asserted-by":"publisher","first-page":"802","DOI":"10.1109\/TLT.2022.3150663","volume":"14","author":"M Andr\u00e9","year":"2021","unstructured":"Andr\u00e9, M., Mello, R.F., Nascimento, A., Lins, R.D., Ga\u0161evi\u0107, D.: Toward automatic classification of online discussion messages for social presence. IEEE Trans. Learn. Technol. 14(6), 802\u2013816 (2021)","journal-title":"IEEE Trans. Learn. Technol."},{"key":"27_CR4","doi-asserted-by":"crossref","unstructured":"Barbosa, G., et al.: Towards automatic cross-language classification of cognitive presence in online discussions. In: Proceedings of the Tenth International Conference on Learning Analytics & Knowledge, pp. 605\u2013614 (2020)","DOI":"10.1145\/3375462.3375496"},{"key":"27_CR5","unstructured":"Boyatzis, R.E.: Transforming Qualitative Information: Thematic analysis and code development. sage (1998)"},{"issue":"1","key":"27_CR6","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45(1), 5\u201332 (2001)","journal-title":"Mach. Learn."},{"key":"27_CR7","doi-asserted-by":"crossref","unstructured":"Cavalcanti, A.P., Diego, A., Mello, R.F., Mangaroska, K., Nascimento, A., Freitas, F., Ga\u0161evi\u0107, D.: How good is my feedback? A content analysis of written feedback. In: Proceedings of the Tenth International Conference on Learning Analytics & Knowledge, pp. 428\u2013437 (2020)","DOI":"10.1145\/3375462.3375477"},{"issue":"6","key":"27_CR8","doi-asserted-by":"publisher","first-page":"799","DOI":"10.3102\/0034654318791584","volume":"88","author":"J Chen","year":"2018","unstructured":"Chen, J., Wang, M., Kirschner, P.A., Tsai, C.C.: The role of collaboration, computer use, learning environments, and supporting strategies in CSCL: a meta-analysis. Rev. Educ. Res. 88(6), 799\u2013843 (2018)","journal-title":"Rev. Educ. Res."},{"key":"27_CR9","doi-asserted-by":"crossref","unstructured":"Chen, T., Guestrin, C.: XGBoost: a scalable tree boosting system. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 785\u2013794 (2016)","DOI":"10.1145\/2939672.2939785"},{"key":"27_CR10","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1016\/j.iheduc.2015.02.001","volume":"25","author":"KH Cheng","year":"2015","unstructured":"Cheng, K.H., Liang, J.C., Tsai, C.C.: Examining the role of feedback messages in undergraduate students\u2019 writing performance during an online peer assessment activity. Internet High. Educ. 25, 78\u201384 (2015)","journal-title":"Internet High. Educ."},{"key":"27_CR11","series-title":"Computer-Supported Collaborative Learning Series","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-65291-3","volume-title":"International Handbook of Computer-Supported Collaborative Learning","year":"2021","unstructured":"Cress, U., Ros\u00e9, C., Wise, A.F., Oshima, J. (eds.): International Handbook of Computer-Supported Collaborative Learning. CCLS, vol. 19. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-65291-3"},{"key":"27_CR12","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"issue":"6","key":"27_CR13","doi-asserted-by":"publisher","DOI":"10.1002\/widm.1332","volume":"9","author":"R Ferreira-Mello","year":"2019","unstructured":"Ferreira-Mello, R., Andr\u00e9, M., Pinheiro, A., Costa, E., Romero, C.: Text mining in education. Wiley Interdisc. Rev. Data Min. Knowl. Discov. 9(6), e1332 (2019)","journal-title":"Wiley Interdisc. Rev. Data Min. Knowl. Discov."},{"key":"27_CR14","doi-asserted-by":"crossref","unstructured":"Ferreira Mello, R., Fiorentino, G., Oliveira, H., Miranda, P., Rakovic, M., Gasevic, D.: Towards automated content analysis of rhetorical structure of written essays using sequential content-independent features in portuguese. In: LAK22: 12th International Learning Analytics and Knowledge Conference, pp. 404\u2013414 (2022)","DOI":"10.1145\/3506860.3506977"},{"issue":"10","key":"27_CR15","doi-asserted-by":"publisher","first-page":"1241","DOI":"10.1080\/01443410.2021.1951671","volume":"41","author":"CJ Fong","year":"2021","unstructured":"Fong, C.J., Schallert, D.L., Williams, K.M., Williamson, Z.H., Lin, S., Kim, Y.W., Chen, L.H.: Making feedback constructive: the interplay of undergraduates\u2019 motivation with perceptions of feedback specificity and friendliness. Educ. Psychol. 41(10), 1241\u20131259 (2021)","journal-title":"Educ. Psychol."},{"issue":"5","key":"27_CR16","doi-asserted-by":"publisher","first-page":"223","DOI":"10.3102\/0013189X11413260","volume":"40","author":"AC Graesser","year":"2011","unstructured":"Graesser, A.C., McNamara, D.S., Kulikowich, J.M.: Coh-metrix: providing multilevel analyses of text characteristics. Educ. Res. 40(5), 223\u2013234 (2011)","journal-title":"Educ. Res."},{"issue":"1","key":"27_CR17","doi-asserted-by":"publisher","first-page":"81","DOI":"10.3102\/003465430298487","volume":"77","author":"J Hattie","year":"2007","unstructured":"Hattie, J., Timperley, H.: The power of feedback. Rev. Educ. Res. 77(1), 81\u2013112 (2007)","journal-title":"Rev. Educ. Res."},{"key":"27_CR18","unstructured":"IBM: What is logistic regression? https:\/\/www.ibm.com\/topics\/logistic-regression (2023). Accessed 3 Jan 2023"},{"key":"27_CR19","doi-asserted-by":"publisher","unstructured":"Jiang, J.: Information extraction from text. In: Aggarwal, C., Zhai, C. (eds), Mining Text Data. Springer, Boston, MA (2012). https:\/\/doi.org\/10.1007\/978-1-4614-3223-4_2","DOI":"10.1007\/978-1-4614-3223-4_2"},{"issue":"4","key":"27_CR20","doi-asserted-by":"publisher","first-page":"344","DOI":"10.1016\/j.learninstruc.2009.08.005","volume":"20","author":"I Kollar","year":"2010","unstructured":"Kollar, I., Fischer, F.: Peer assessment as collaborative learning: a cognitive perspective. Learn. Instr. 20(4), 344\u2013348 (2010)","journal-title":"Learn. Instr."},{"issue":"3","key":"27_CR21","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1016\/S0747-5632(02)00057-2","volume":"19","author":"K Kreijns","year":"2003","unstructured":"Kreijns, K., Kirschner, P.A., Jochems, W.: Identifying the pitfalls for social interaction in computer-supported collaborative learning environments: a review of the research. Comput. Hum. Behav. 19(3), 335\u2013353 (2003)","journal-title":"Comput. Hum. Behav."},{"key":"27_CR22","doi-asserted-by":"crossref","unstructured":"Landis, J.R., Koch, G.G.: The measurement of observer agreement for categorical data. biometrics 33(1), 159\u2013174 (1977)","DOI":"10.2307\/2529310"},{"key":"27_CR23","unstructured":"Lee, A., Lim, T.M.: Mining opinions from university students\u2019 feedback using text analytics. Inf. Technol. Ind. 4(1), 26\u201333 (2016)"},{"issue":"2","key":"27_CR24","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1080\/02602938.2019.1620679","volume":"45","author":"H Li","year":"2020","unstructured":"Li, H., Xiong, Y., Hunter, C.V., Guo, X., Tywoniw, R.: Does peer assessment promote student learning? A meta-analysis. Assess. Eval. High. Educ. 45(2), 193\u2013211 (2020)","journal-title":"Assess. Eval. High. Educ."},{"issue":"3","key":"27_CR25","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1080\/02602930701292548","volume":"33","author":"A Lizzio","year":"2008","unstructured":"Lizzio, A., Wilson, K.: Feedback on assessment: students\u2019 perceptions of quality and effectiveness. Assess. Eval. High. Educ. 33(3), 263\u2013275 (2008)","journal-title":"Assess. Eval. High. Educ."},{"issue":"04","key":"27_CR26","doi-asserted-by":"publisher","first-page":"197","DOI":"10.4236\/ojml.2017.74015","volume":"7","author":"Y Luo","year":"2017","unstructured":"Luo, Y., Liu, Y., et al.: Comparison between peer feedback and automated feedback in college English writing: a case study. Open J. Mod. Linguist. 7(04), 197 (2017)","journal-title":"Open J. Mod. Linguist."},{"issue":"3","key":"27_CR27","doi-asserted-by":"publisher","first-page":"352","DOI":"10.1080\/14703297.2018.1555049","volume":"57","author":"Z Ma","year":"2020","unstructured":"Ma, Z., Yan, X., Wang, Q.: Assessing individual contribution in collaborative learning through self-and peer-assessment in the context of china. Innovations Educ. Teach. Int. 57(3), 352\u2013363 (2020)","journal-title":"Innovations Educ. Teach. Int."},{"key":"27_CR28","unstructured":"Manning, C., Schutze, H.: Foundations of Statistical Natural Language Processing. MIT Press, Cambridge (1999)"},{"issue":"06","key":"27_CR29","doi-asserted-by":"publisher","first-page":"419","DOI":"10.3414\/ME13-01-0122","volume":"53","author":"A Mayr","year":"2014","unstructured":"Mayr, A., Binder, H., Gefeller, O., Schmid, M.: The evolution of boosting algorithms. Methods Inf. Med. 53(06), 419\u2013427 (2014)","journal-title":"Methods Inf. Med."},{"issue":"3","key":"27_CR30","doi-asserted-by":"publisher","first-page":"276","DOI":"10.11613\/BM.2012.031","volume":"22","author":"ML McHugh","year":"2012","unstructured":"McHugh, M.L.: Interrater reliability: the kappa statistic. Biochemia Med. 22(3), 276\u2013282 (2012)","journal-title":"Biochemia Med."},{"issue":"1","key":"27_CR31","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1177\/0741088309351547","volume":"27","author":"DS McNamara","year":"2010","unstructured":"McNamara, D.S., Crossley, S.A., McCarthy, P.M.: Linguistic features of writing quality. Written Commun. 27(1), 57\u201386 (2010)","journal-title":"Written Commun."},{"issue":"4","key":"27_CR32","doi-asserted-by":"publisher","first-page":"292","DOI":"10.1080\/01638530902959943","volume":"47","author":"DS McNamara","year":"2010","unstructured":"McNamara, D.S., Louwerse, M.M., McCarthy, P.M., Graesser, A.C.: Coh-metrix: capturing linguistic features of cohesion. Discourse Process. 47(4), 292\u2013330 (2010)","journal-title":"Discourse Process."},{"key":"27_CR33","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1007\/s11251-008-9053-x","volume":"37","author":"MM Nelson","year":"2009","unstructured":"Nelson, M.M., Schunn, C.D.: The nature of feedback: how different types of peer feedback affect writing performance. Instr. Sci. 37, 375\u2013401 (2009)","journal-title":"Instr. Sci."},{"key":"27_CR34","doi-asserted-by":"crossref","unstructured":"Nick, T.G., Campbell, K.M.: Logistic regression. Top. Biostatistics 404, 273\u2013301 (2007)","DOI":"10.1007\/978-1-59745-530-5_14"},{"key":"27_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.caeai.2022.100059","volume":"3","author":"I Osakwe","year":"2022","unstructured":"Osakwe, I., Chen, G., Whitelock-Wainwright, A., Ga\u0161evi\u0107, D., Cavalcanti, A.P., Mello, R.F.: Towards automated content analysis of educational feedback: a multi-language study. Comput. Educ. Artif. Intell. 3, 100059 (2022)","journal-title":"Comput. Educ. Artif. Intell."},{"key":"27_CR36","doi-asserted-by":"publisher","first-page":"160940691989922","DOI":"10.1177\/1609406919899220","volume":"19","author":"C O\u2019Connor","year":"2020","unstructured":"O\u2019Connor, C., Joffe, H.: Intercoder reliability in qualitative research: debates and practical guidelines. Int. J. Qual. Methods 19, 1609406919899220 (2020)","journal-title":"Int. J. Qual. Methods"},{"issue":"2","key":"27_CR37","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/j.chb.2009.10.011","volume":"26","author":"C Phielix","year":"2010","unstructured":"Phielix, C., Prins, F.J., Kirschner, P.A.: Awareness of group performance in a CSCL-environment: effects of peer feedback and reflection. Comput. Hum. Behav. 26(2), 151\u2013161 (2010)","journal-title":"Comput. Hum. Behav."},{"issue":"4","key":"27_CR38","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1080\/02602930500099219","volume":"30","author":"FJ Prins","year":"2005","unstructured":"Prins, F.J., Sluijsmans, D.M., Kirschner, P.A., Strijbos, J.W.: Formative peer assessment in a CSCL environment: a case study. Assess. Eval. High. Educ. 30(4), 417\u2013444 (2005)","journal-title":"Assess. Eval. High. Educ."},{"key":"27_CR39","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-319-99722-3_1","volume-title":"Computational Processing of the Portuguese Language","author":"KS dos Santos","year":"2018","unstructured":"dos Santos, K.S., Soder, M., Marques, B.S.B., Feltrim, V.D.: Analyzing the rhetorical structure of opinion articles in the context of a Brazilian college entrance examination. In: Villavicencio, A. (ed.) PROPOR 2018. LNCS (LNAI), vol. 11122, pp. 3\u201312. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-99722-3_1"},{"key":"27_CR40","doi-asserted-by":"publisher","first-page":"706","DOI":"10.1007\/s11162-020-09591-y","volume":"61","author":"BA Simonsmeier","year":"2020","unstructured":"Simonsmeier, B.A., Peiffer, H., Flaig, M., Schneider, M.: Peer feedback improves students\u2019 academic self-concept in higher education. Res. High. Educ. 61, 706\u2013724 (2020)","journal-title":"Res. High. Educ."},{"key":"27_CR41","first-page":"93","volume":"2","author":"C Sutton","year":"2006","unstructured":"Sutton, C., McCallum, A.: An introduction to conditional random fields for relational learning. Introduction Stat. Relational Learn. 2, 93\u2013128 (2006)","journal-title":"Introduction Stat. Relational Learn."},{"key":"27_CR42","doi-asserted-by":"publisher","DOI":"10.1016\/j.compedu.2022.104467","volume":"187","author":"JS Tan","year":"2022","unstructured":"Tan, J.S., Chen, W.: Peer feedback to support collaborative knowledge improvement: what kind of feedback feed-forward? Comput. Educ. 187, 104467 (2022)","journal-title":"Comput. Educ."},{"issue":"1","key":"27_CR43","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1177\/0261927X09351676","volume":"29","author":"YR Tausczik","year":"2010","unstructured":"Tausczik, Y.R., Pennebaker, J.W.: The psychological meaning of words: LIWC and computerized text analysis methods. J. Lang. Soc. Psychol. 29(1), 24\u201354 (2010)","journal-title":"J. Lang. Soc. Psychol."},{"key":"27_CR44","unstructured":"Van Wissen, L., Boot, P.: An electronic translation of the LIWC dictionary into Dutch. In: Electronic Lexicography in the 21st Century: Proceedings of eLex 2017 Conference, pp. 703\u2013715. Lexical Computing (2017)"},{"key":"27_CR45","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1007\/978-3-030-23884-1_17","volume-title":"Methodologies and Intelligent Systems for Technology Enhanced Learning, 9th International Conference, Workshops","author":"O Viberg","year":"2019","unstructured":"Viberg, O., Mavroudi, A., Fernaeus, Y., Bogdan, C., Laaksolahti, J.: Reducing free riding: CLASS \u2013 a system for collaborative learning assessment. In: Popescu, E., Bel\u00e9n Gil, A., Lancia, L., Simona Sica, L., Mavroudi, A. (eds.) MIS4TEL 2019. AISC, vol. 1008, pp. 132\u2013138. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-23884-1_17"},{"key":"27_CR46","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1007\/978-3-030-23884-1_17","volume-title":"Methodologies and Intelligent Systems for Technology Enhanced Learning, 9th International Conference, Workshops","author":"O Viberg","year":"2020","unstructured":"Viberg, O., Mavroudi, A., Fernaeus, Y., Bogdan, C., Laaksolahti, J.: Reducing free riding: CLASS \u2013 a system for collaborative learning assessment. In: Popescu, E., Bel\u00e9n Gil, A., Lancia, L., Simona Sica, L., Mavroudi, A. (eds.) MIS4TEL 2019. AISC, vol. 1008, pp. 132\u2013138. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-23884-1_17"},{"key":"27_CR47","doi-asserted-by":"crossref","unstructured":"Yang, Y., Liu, X.: A re-examination of text categorization methods. In: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 42\u201349 (1999)","DOI":"10.1145\/312624.312647"},{"issue":"1","key":"27_CR48","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1007\/s11412-021-09339-5","volume":"16","author":"S Zhang","year":"2021","unstructured":"Zhang, S., Chen, J., Wen, Y., Chen, H., Gao, Q., Wang, Q.: Capturing regulatory patterns in online collaborative learning: a network analytic approach. Int. J. Comput. Support. Collaborative Learn. 16(1), 37\u201366 (2021). https:\/\/doi.org\/10.1007\/s11412-021-09339-5","journal-title":"Int. J. Comput. Support. Collaborative Learn."}],"container-title":["Lecture Notes in Computer Science","Responsive and Sustainable Educational Futures"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-42682-7_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T13:58:43Z","timestamp":1762091923000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-42682-7_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031426810","9783031426827"],"references-count":48,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-42682-7_27","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"28 August 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EC-TEL","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Technology Enhanced Learning","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Aveiro","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ectel2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ea-tel.eu\/ectel2023","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}