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title = "Measuring Students’ Acceptance to AI-Driven Assessment in eLearning: Proposing a First TAM-Based Research Model"
date = 2019-06-01
draft = false

# Authors. Comma separated list, e.g. `["Bob Smith", "David Jones"]`.

authors = ["Juan Cruz-Benito", "José Carlos Sánchez-Prieto", "Roberto Therón", "Francisco J. García-Peñalvo"]

# Publication type.

# Legend:

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# 1 = Conference paper
# 2 = Journal article
# 3 = Manuscript
# 4 = Report
# 5 = Book
# 6 = Book section

publication_types = ["1"]

# Publication name and optional abbreviated version.

publication = "In _International Conference on Learning and Collaboration Technologies_. HCI International 2019. _Learning and Collaboration Technologies. Designing Learning Experiences_ Lecture Notes in Computer Science, vol 11590. Springer, Cham"

# publication*short = "In \_HCII 2019*"

# Abstract and optional shortened version.

abstract = "Artificial Intelligence is one of the trend areas in research. It is applied in many different contexts successfully. One of the contexts where Artificial Intelligence is applied is in Education. In the literature, we find several works in the last years that explore the application of Artificial Intelligence-related techniques to analyze students’ behavior, to enable virtual tutors or to assess the learning. However, what are the students’ perceptions on this subject of Artificial Intelligence and Education? Do they accept the use of Artificial Intelligence techniques to assess their learning? Are they reluctant to be influenced by non-human agents in such a human process like education? To try to respond to these questions, this paper presents a novel proposal of a research model based on the Technology Acceptance Model. To describe the model, we present its different main constructs and variables, as well as the hypotheses to analyze, adapted to the object of study. Finally, we discuss the main implications of this research model, the opportunities that could come based on this proposal and the future of this research."
abstract_short = ""

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selected = false

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# projects = ["internal-project"]

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tags = ["Artificial intelligence","Technology acceptance model","Education","eLearning","Students"]

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#url_pdf = "#"
#url_preprint = ""
#url_code = "#"
#url_dataset = "#"
#url_project = "#"
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url_source = "https://link.springer.com/chapter/10.1007%2F978-3-030-21814-0_2"

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doi = "10.1007/978-3-030-21814-0_2"

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math = true

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[image]

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focal_point = ""
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