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Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
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Humans are very diverse and although we share many similarities, we also have many differences. The social groups we belong to help form our identities (Tajfel, 1974). These differences may be difficult for some people to reconcile, which may lead to prejudice toward people who are different. Prejudice is a negative attitude and feeling toward an individual based solely on one’s membership in a particular social group (Allport, 1954; Brown, 2010). Prejudice is common against people who...
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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
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The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
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Integrating Multiculturalism Into Artificial Intelligence-Assisted Programming Lessons: Examining Inter-Ethnicity

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  • 1Department of Computer Science and Information Engineering, National Taitung University, Taitung City, Taiwan.

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Summary
This summary is machine-generated.

Cultural background significantly impacts college students' learning motivation and performance in computer programming. Indigenous students worried about community impact, while Han Chinese students focused on personal career value.

Keywords:
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Area of Science:

  • Computer Science Education
  • Multicultural Education
  • Artificial Intelligence in Education

Background:

  • Colleges are making programming compulsory for all students due to increasing digitization.
  • Ethnic and cultural backgrounds influence students' learning experiences and motivations in programming.

Purpose of the Study:

  • To compare learning expectancy, motivation, and effectiveness in programming among multi-ethnic college students.
  • To analyze differences in theoretical and actual learning performance using an AI-assisted module.

Main Methods:

  • Developed an AI-assisted programming module utilizing deep learning networks.
  • Analyzed student learning processes, error types, and cognitive learning theory.
  • Conducted an experiment with 96 multi-ethnic college students.

Main Results:

  • Significant differences found in theoretical performance, expectancy, and motivation between ethnic groups.
  • Indigenous students' concerns about community impact affected their learning outcomes.
  • Han Chinese students' motivation was driven by perceived personal value of programming.

Conclusions:

  • Understanding multicultural influences is crucial for effective computer programming education.
  • Tailoring teaching methods to diverse student backgrounds can improve learning.
  • Findings provide a reference for integrating multiculturalism into programming curricula.