Education 2.0: Artificial Intelligence and the End of the Test

Kalantzis, Bill Cope and Mary

doi:10.1163/25902539-00102009

Cited by 16 publications

(6 citation statements)

References 17 publications

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“…AI can facilitate learners' engagement with computer-mediated content resources, interactions with peers and teachers and knowledge representations in the form of student work. Cope and Kalantzis (2019) found that AI helps both learners and teachers to monitor incremental progress and may support customised or adaptive learning. Moodle Guenole and Feinzig (2018) Helps learner to identify mistakes and suggest corrections Ferguson (2012) Supports in learning course, evaluate the personal system, management of academic data Frasson and Aı«meur (1998) Strategic interface in the instruction design Cope et al (2020) Learning assessment and recursive feedback system Cope and Kalantzis (2019) Progress monitoring, learning customisation can also help in learning assessment by replacing the traditional assessment process with recursive feedback systems that are integral to learning (Cope et al, 2020).…”

Section: Q2mentioning

confidence: 99%

“…Despite the high demand and urgent application of AI in L&D, very little structured research is available. Most of the available research is conducted on education (Cope et al , 2020; Cope and Kalantzis, 2019) and very few are shown in the training context. Management research on AI using systematic literature review (SLR) methods is limited and mostly confined to workplace outcomes (Pereira et al , 2021), supply chain Toorajipour et al (2021), business strategy (Borges et al , 2021), fake news (Al-Asadi and Tasdemir, 2022), human resources (Votto et al , 2021) and recruitment (Nawaz, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Artificial intelligence in learning and development: a systematic literature review

Bhatt

Muduli

2022

EJTD

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Purpose The presented research explored artificial intelligence (AI) application in the learning and development (L&D) function. Although a few studies reported AI and the people management processes, a systematic and structured study that evaluates the integration of AI with L&D focusing on scope, adoption and affecting factors is mainly absent. This study aims to explore L&D-related AI innovations, AI’s role in L&D processes, advantages of AI adoption and factors leading to effective AI-based learning following the analyse, design, develop, implement and evaluate approach. Design/methodology/approach The presented research has adopted a systematic literature review method to critically analyse, synthesise and map the extant research by identifying the broad themes involved. The review approach includes determining a time horizon, database selection, article selection and article classification. Databases from Emerald, Sage, Francis and Taylor, etc. were used, and the 81 research articles published between 1996 and 2022 were identified for analysis. Findings The result shows that AI innovations such as natural language processing, artificial neural networks, interactive voice response and text to speech, speech to text, technology-enhanced learning and robots can improve L&D process efficiency. One can achieve this by facilitating the articulation of learning module, identifying learners through face recognition and speech recognition systems, completing course work, etc. Further, the result also shows that AI can be adopted in evaluating learning aptitude, testing learners’ memory, tracking learning progress, measuring learning effectiveness, helping learners identify mistakes and suggesting corrections. Finally, L&D professionals can use AI to facilitate a quicker, more accurate and cheaper learning process, suitable for a large learning audience at a time, flexible, efficient, convenient and less expensive for learners. Originality/value In the absence of any systematic research on AI in L&D function, the result of this study may provide useful insights to researchers and practitioners.

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Section: Q2mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Artificial intelligence in learning and development: a systematic literature review

Bhatt

Muduli

2022

EJTD

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“…At the University of Illinois, we've been researching this transformation, and developing and testing online learning solutions (Cope & Kalantzis, 2017). As senior professors in a historically residential university, for some years we have only taught online.…”

Section: Mary Kalantzis and Bill Copementioning

confidence: 99%

“…Embedded, on-the-fly formative assessments can track community engagement and personal progress. An example: in one of our recent 8-week courses with 54 students, using our CGScholar platform there were 14,500 pieces of actionable feedback on 3.3 million datapoints, giving students and instructors a far richer and more reliable picture of learning than ever possible with a traditional test (Cope & Kalantzis 2019).…”

Section: Create Pedagogies Of Intense Engagementmentioning

confidence: 99%

After the COVID-19 crisis: Why higher education may (and perhaps should) never be the same

Cope

Kalantzis

2020

ACCESS: Contemporary Issues in Education

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Universities and colleges have dragged their feet making the move to online teaching and learning. Suddenly, with this COVID-19 crisis, everyone had to move online. Few universities or colleges are prepared for such a rapid shift. Meanwhile, the conventional wisdom remains - the gold-standard for learning is traditional face-to-face, while online is second-best. But perhaps, even without COVID-19, in-person learning is ripe for radical transformation. At the University of Illinois, we’ve been researching this transformation, and developing and testing online learning solutions. Simply put, online can be completely different, and with the right tools, potentially much superior to in-person teaching. To reap the benefits of online learning, we need to abandon the current generation educational technologies—systems and processes that mostly do little more than reverse-engineer traditional classrooms.

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“…Mais importante do que a memória cumulativa do aprendizado conteudista, será o pensamento de ordem superior, capaz de criticar, de ser criativo e de se autoanalisar para tomar decisões de aprendizagem. Em vez de mentes puramente individuais, a mente social será reconhecida a partir da procedência, da veracidade do conhecimento e das contribuições colaborativas dos pares no processo de aprendizagem (COPE; KALANTZIS, 2017KALANTZIS, , 2019COPE, 2020).…”

Section: Mediações E Letramentos Em Fluxounclassified

Transletramento, metaletramento e letramentos transmidiáticos

Silene Câmara Lassalvia

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Para minha querida amiga profa. Dra. Soledad Galhardo, que nos deixou muito cedo, mas que é, ainda, uma das pessoas mais inspiradoras que eu conheci. AGRADECIMENTOSAos professores e professoras que contribuiram muito nessa jornada... À profa Dra Roxane Rojo, que me acolheu no IEL, ainda como aluna especial, e me apresentou o mundo dos letramentos com assertividade e brilho no olhar. Obrigada! Aos professores que aceitaram participar das bancas de qualificação e de defesa da Tese, pelos questionamentos, ponderações, sugestões e partilha de conhecimento e de referências. Obrigada, profa.

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Education 2.0: Artificial Intelligence and the End of the Test

Cited by 16 publications

References 17 publications

Artificial intelligence in learning and development: a systematic literature review

Artificial intelligence in learning and development: a systematic literature review

After the COVID-19 crisis: Why higher education may (and perhaps should) never be the same

Transletramento, metaletramento e letramentos transmidiáticos

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