E-Learning Technology Incentive Factors and Behavioral Intentions Toward Computer-Based and Game-Based Assessment–Model Inventory

Abstract

This measurement model, titled the E-Learning Technology Incentive Factors and Behavioral Intentions Toward Computer-Based and Game-Based Assessment–Model, was developed to empirically investigate student responses to modern digital assessment methods. Specifically, the study focused on comparing the impact of two distinct formative assessment (FA) tools: Computer-Based Assessment (CBA) and Game-Based Assessment (GBA).

The core objective was to map how various technological incentives influence students’ learning perception, behavioral intention, and overall academic achievement over the course of an academic term. The instrument utilized items adapted from established research frameworks, and its psychometric properties (factor structure, reliability, and validity) were confirmed using a sample of university students in Taiwan.

Keywords

Behavioral Intentions, Computer-Based Assessments, Game-Based Assessments, E-Learning Technology Incentives, Performance Expectancy, Effort Expectancy, Social Influence, Perceived Playfulness, User Acceptance, Educational Measures, Human Computer Interaction, Formative Assessment, Digital Game-Based Learning, Technology Acceptance, Student Attitudes.

Authors

Lin, Jian-Wei, Tsai, Chia-Wen, Hsu, Chu-Ching.

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Purpose

The primary purpose of this measurement inventory is to systematically evaluate the effects of digital formative assessment tools—specifically Computer-Based Assessment (CBA) and Game-Based Assessment (GBA)—on key educational outcomes. These outcomes include students’ learning perception, their resultant behavioral intention to use the systems, their actual use behavior, and their eventual learning achievement.

The model is designed to capture these effects across different stages of the learning process: the early stage (prior to the mid-term examination) and the late stage (leading up to the final term examination), allowing for a longitudinal analysis of technology adoption and efficacy within e-learning environments.

Construct

The scale measures constructs central to technology adoption and educational psychology, generally categorized under three broad headings:

• E-Learning Technology Incentives: Factors that motivate students to use the technology, encompassing Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Perceived Playfulness (PP).

• Assessment Modalities: The comparison between Computer-Based Assessment (CBA) and Game-Based Assessment (GBA).

• Behavioral Intentions: The likelihood or willingness of students to continue using the assessment technologies in future academic settings.

Validity

The construct validity of the model was rigorously established through the application of factor analysis. This statistical procedure confirmed that the items grouped coherently under their intended theoretical constructs, providing strong structural validity for the overall measurement model.

The specific findings from the factor analysis indicated that all individual scale items demonstrated high validity, with factor loadings consistently exceeding the threshold of 0.7. This high loading suggests that each item strongly contributes to defining its respective latent construct.

Reliability

Internal consistency, a crucial measure of reliability, was assessed using Cronbach’s alpha for all constructs within the inventory. The analysis revealed robust reliability across the measurement model, supporting the internal coherence of the instrument.

The resulting Cronbach’s alpha values for the various constructs ranged consistently between 0.76 and 0.76. These values confirm that the items within each construct are highly correlated and reliably measure the same underlying dimension.

Factor Analysis

A comprehensive factor analysis was conducted to confirm the theoretical structure derived from the adapted measurement items. This method was essential for validating the underlying factor structure and ensuring that the instrument was measuring the intended constructs (Performance Expectancy, Effort Expectancy, Social Influence, Perceived Playfulness, and Behavioral Intention).

The analysis yielded strong psychometric results, demonstrating acceptable validity. All items exhibited factor loadings greater than 0.7, confirming that the measurement model possesses a stable and justifiable factor structure.

Instrument

Test Type: This is an original instrument, classified as an Inventory/Questionnaire.

Format: Items are rated using a 5-point Likert-type scale, typically ranging from 1 (strongly disagree) to 5 (strongly agree).

Language Available: The instrument is available in English.

Population Group: Human (Male and Female).

Age Group: Adulthood (18 years and older), specifically Young Adulthood (18–29 years).

Population Details: The scale was validated using a specific sample of university students located in Taiwan.

Test Methodology: The development and evaluation process utilized a comprehensive psychometric approach, including analyses of Test Validity, Construct Validity, Test Reliability, Internal Consistency, Factor Analysis, and the creation of a structural Measurement Model.

Keywords

Behavioral Intentions, Computer-Based Assessments, Game-Based Assessments, E-Learning Technology Incentives, Performance Expectancy, Effort Expectancy, Social Influence, Perceived Playfulness, User Acceptance, Educational Measures, Human Computer Interaction, Social Influences, Student Attitudes, Electronic Learning, Computerized Assessment, Formative Assessment, Digital Game-Based Learning, Technology Acceptance.

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Authors

Author ORCID Identifier: Tsai, Chia-Wen: http://orcid.org/0000-0002-6698-7747

Affiliation Email addresses: Lin, Jian-Wei: [email protected]

Correspondence Address: Lin, Jian-Wei: [email protected]

Affiliations:

• Lin, Jian-Wei: Chien Hsin University of Science and Technology, Department of International Business.

• Tsai, Chia-Wen: Ming Chuan University, Department of Information Management.

• Hsu, Chu-Ching: Chien Hsin University of Science and Technology, Department of Applied Foreign Languages.

Permissions & Fee and Test Year

Permissions: Contact Publisher

Commercial: No

Fee: No

Test Year: 2023

Reference’s

Lin, J.-W., Tsai, C.-W., & Hsu, C.-C. (2023). A comparison of computer-based and game-based formative assessments: A long-term experiment. Interactive Learning Environments, 31(2), 938–954. DOI: https://doi.org/10.1080/10494820.2020.1815219

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Items of the E-Learning Technology Incentive Factors and Behavioral Intentions Toward Computer-Based and Game-Based Assessment–Model Inventory

This inventory consists of 15 items organized under five primary constructs: Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Perceived Playfulness (PP), and Behavioural Intention (BI). All items are rated on a 5-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). The full set of items is available in the source reference publication by Lin, Tsai, & Hsu (2023), specifically located in Table 1 on page 945.