Development of AI Literacy Instruments to Map Elementary School Students' Abilities

ADDIE Model

The ADDIE model is a systematic approach developed to produce effective learning products. This model is not only applied in the development of learning media but is also used in curriculum design, digital learning system development, module preparation, and training programs for educators. Therefore, ADDIE is often regarded as a foundational framework in instructional design due to its flexibility and applicability across various learning contexts (Rahayu 2025). The ADDIE model is a concept applied to build basic performance in the learning process, particularly in developing learning product designs. This model is part of instructional design oriented towards individual learning, encompassing stages that include short-term and long-term goals, arranged systematically, and adopting a systems approach to knowledge and the human learning process (Hidayat and Muhamad 2021).

This study involved two groups of participants: experts and students. Four experts were involved in validating the developed AI literacy instrument; they are specialists in elementary education with competencies in instrument development and learning evaluation. The research subjects consisted of 100 elementary school students who had access to electronic devices and were familiar with using AI-based digital applications. Data collection was conducted using a questionnaire developed by the researcher, used to assess aspects of students' AI literacy, including the ability to recognize, understand, use, evaluate, and create with AI in the learning context, while also gathering input from experts regarding content and construct validity. The instrument, once declared valid and reliable, was then used for data collection from the student subjects (Torang Siregar, & Yuni Rhamayanti. (2025). This instrument consisted of statements that students had to answer honestly, based on a grid developed from the aspects of AI literacy: the ability to recognize AI, understand AI, use and apply AI, evaluate and create with AI, and the attitudes and ethics in using AI. The development of the instrument based on this grid aimed to ensure that each statement item was relevant to the measured indicator and appropriate for the cognitive development level and experiences of elementary school students in utilizing AI technology, as detailed in Table 1.

The research instrument was a questionnaire developed based on five dimensions of students' abilities in AI as follows:

TABLE 1. AI Literacy Instrument Grid

I know several applications that use AI. use AI features

The AI Literacy Instrument Grid presented in Table 1 reflects a comprehensive framework for assessing students’ competencies in interacting with artificial intelligence across multiple dimensions. The instrument is systematically organized into five major indicators, namely recognizing AI, understanding AI, applying AI, evaluating and creating with AI, and AI ethics. Each indicator is further elaborated into several sub-indicators that capture specific aspects of students’ literacy. These sub-indicators are operationalized into measurable questionnaire items to ensure clarity and consistency in data collection. The structure of the instrument demonstrates alignment with contemporary frameworks of digital and AI literacy. It also emphasizes not only technical knowledge but also critical thinking and ethical awareness. Such a multidimensional approach is crucial in the current educational landscape where AI integration is rapidly increasing. Therefore, this instrument serves as a robust tool to evaluate students’ readiness in engaging with AI technologies. (Zhang, H., Perry, A. & Lee, I., 2025)

The first indicator, recognizing AI, focuses on students’ ability to identify and be aware of AI technologies in their daily lives. This includes the capacity to mention examples of AI-based applications such as conversational agents and intelligent systems. Students are also expected to recognize outputs generated by AI, including images, text, and videos. The ability to distinguish AI-generated content from human-created content is increasingly important in the digital era. Furthermore, recognizing AI involves awareness of various applications and platforms that incorporate AI features. The inclusion of game-based applications highlights the relevance of AI in entertainment contexts familiar to students. Identifying symbols or icons associated with AI functionalities also reflects a practical understanding of user interfaces. Altogether, this indicator establishes foundational awareness, which is essential before deeper comprehension can occur. (Faizal, Khoirunnisa, & Budiono, H., 2025)

The second indicator, understanding AI, emphasizes conceptual knowledge regarding how AI operates. Students are expected to explain AI processes in simple terms, demonstrating basic comprehension of algorithms and data-driven mechanisms. This includes understanding that AI systems can automatically respond to queries based on programmed models. Importantly, students are introduced to the concept that AI learns from data, which implies potential inaccuracies in its outputs. This awareness is critical in preventing blind trust in AI-generated information. Additionally, understanding AI includes recognizing its generative capabilities, such as creating images or text. Students must also acknowledge the limitations of AI, particularly the absence of emotions and human-like consciousness. This distinction helps in fostering realistic expectations regarding AI functionalities. Consequently, this indicator supports the development of informed and critical users of AI. (Zhang, H., Perry, A. & Lee,

I., 2025) The third indicator, applying AI, relates to students’ practical ability to use AI tools in various contexts. This involves independent operation of AI applications without external assistance, reflecting digital autonomy. Students are also expected to utilize AI for information retrieval, which enhances their research capabilities. The use of AI in generating creative outputs, such as ideas and explanations, indicates its role as a cognitive support tool. Additionally, AI can be used to verify answers, thereby assisting in self-assessment and learning validation. The integration of AI into academic tasks demonstrates its potential in enhancing productivity and efficiency. However, proper guidance is necessary to ensure that students use AI appropriately. This indicator highlights the importance of hands-on experience in building AI literacy. Ultimately, applying AI bridges the gap between theoretical knowledge and real-world practice. (Faizal, Khoirunnisa, & Budiono, H., 2025) The fourth indicator, evaluating and creating with AI, represents higher-order thinking skills in Bloom’s taxonomy. Students are required to formulate effective prompts to guide AI outputs according to their needs. This skill is essential for maximizing the utility of AI systems. Additionally, students must

compare AI-generated responses with other sources of knowledge to assess accuracy and reliability. This critical evaluation process helps in mitigating misinformation risks. Combining personal ideas with AI-generated content reflects creative collaboration between humans and machines. Students are also encouraged to produce visual outputs such as posters or illustrations using AI tools. Revising AI outputs to meet specific requirements demonstrates iterative thinking and problem-solving skills. Thus, this indicator promotes both analytical and creative competencies in AI use. (Zhang, H., Perry, A. & Lee, I.,

2025. The fifth indicator, AI ethics, underscores the importance of responsible and ethical use of AI technologies. Students are expected to use AI safely, particularly by protecting personal data and privacy. Ethical awareness includes understanding the potential risks associated with data misuse. Moreover, students should use AI for positive and constructive purposes, especially in educational contexts. The emphasis on polite communication with AI reflects digital etiquette and respectful interaction. Importantly, students are guided to use AI as a learning aid rather than a tool for academic dishonesty. Avoiding direct copying of AI-generated answers fosters originality and intellectual integrity. This indicator ensures that AI literacy is not limited to technical skills but also encompasses moral considerations. Consequently, ethical competence becomes a fundamental aspect of AI literacy. (Faizal, Khoirunnisa, & Budiono, H., 2025) The use of a Likert scale ranging from 1 to 4 provides a structured approach to measuring students’ responses. This scale allows for the assessment of varying levels of agreement or ability. By avoiding a neutral midpoint, the instrument encourages more definitive responses from participants. This design enhances the reliability of the collected data. Each item is scored and subsequently averaged to represent students’ proficiency in each AI literacy dimension. The quantitative nature of the scale facilitates statistical analysis and interpretation. Furthermore, it allows for comparisons across different groups or contexts. Thus, the Likert scale serves as an effective measurement tool in this study. (Yim, I.H.Y., Su, J., 2025) The data analysis method employed is descriptive quantitative analysis, which focuses on summarizing and interpreting numerical data. This approach is appropriate for identifying trends and patterns in students’ AI literacy levels. By calculating mean scores for each indicator, researchers can determine areas of strength and weakness. The analysis also provides insights into overall competency levels across the five dimensions. Descriptive statistics such as averages are useful for presenting findings in a clear and concise manner. Additionally, this method supports evidence-based conclusions regarding students’ abilities. The results can be used to inform educational strategies and interventions. Therefore, descriptive analysis plays a crucial role in translating raw data into meaningful insights. (Yim, I.H.Y., Su, J., 2025) The integration of AI literacy into education reflects the growing importance of digital competencies in the 21st century. As AI technologies become more prevalent, students must be equipped with the skills to engage with them effectively. The instrument outlined in Table 1 aligns with this need by covering both cognitive and practical aspects of AI use. It also emphasizes critical evaluation and ethical considerations, which are often overlooked in traditional digital literacy frameworks. By incorporating these dimensions, the instrument provides a holistic assessment of AI literacy. This is particularly relevant in preparing students for future academic and professional environments. Consequently, the instrument contributes to the advancement of modern educational practices. (Yim, I.H.Y., Su, J., 2025) Another significant aspect of this instrument is its adaptability to various educational levels. The items are designed in a way that they can be easily understood by students with different backgrounds. This makes the instrument versatile and applicable in diverse contexts. Teachers can also modify or expand

the items בהתאם to specific learning objectives. The flexibility of the instrument enhances its practical utility in classroom settings. Moreover, it can serve as a diagnostic tool to identify students’ needs and tailor instruction accordingly. This adaptability ensures that the instrument remains relevant in dynamic educational environments. Hence, it supports continuous improvement in teaching and learning processes. (Yim, I.H.Y., Su, J., 2025)

The role of AI in supporting learning activities is increasingly evident through this framework. AI tools can assist students in understanding complex concepts by providing explanations and examples. They also facilitate personalized learning experiences based on individual needs. The ability to generate creative content enhances students’ engagement and motivation. However, without proper literacy, students may misuse these tools or rely on them excessively. The instrument addresses this issue by promoting balanced and responsible use of AI. It encourages students to view AI as a supportive tool rather than a substitute for thinking. Therefore, AI literacy becomes essential in maximizing the benefits of technology in education. (Yim, I.H.Y., Su, J., 2025)

In addition, the emphasis on critical evaluation within the instrument is particularly महत्वपूर्ण. Students are trained to question and verify AI-generated information לפני accepting it as accurate. This skill is essential in an era where misinformation can spread rapidly through digital platforms. By comparing AI outputs with credible sources, students develop analytical thinking abilities. This process also reinforces traditional research skills in a modern context. Furthermore, it fosters a sense of responsibility in using digital information. The ability to critically evaluate AI outputs is a key component of digital citizenship. Thus, the instrument contributes to the development of informed and responsible learners. (Yue, M., Jong, M. S. Y., Dai, Y., & Lau, W. W. F., 2025)

The creative dimension of AI literacy highlighted in this instrument is equally important. Students are encouraged to use AI as a tool for innovation and expression. This includes generating visual and textual content that reflects their ideas. The combination of human creativity and AI capabilities can lead to unique and meaningful outputs. This collaborative approach enhances students’ confidence and problem-solving skills. It also prepares them for future careers where creativity and technology intersect. By fostering creativity, the instrument supports holistic student development. Consequently, it aligns with modern educational goals that emphasize innovation. (Yim, I.H.Y., Su, J., 2025)

Ethical considerations remain a central theme throughout the instrument. As AI technologies evolve, ethical challenges become more complex. Students must be aware of issues such as data privacy, bias, and academic integrity. The instrument addresses these concerns by incorporating specific items المتعلقة ethical behavior. This ensures that students not only use AI effectively but also responsibly. Ethical literacy is essential in building trust and accountability in digital environments. It also helps prevent potential misuse of AI technologies. Therefore, the inclusion of ethics strengthens the overall framework of AI literacy. (Yue, M., Jong, M. S. Y., Dai, Y., & Lau, W. W. F., 2025)

The findings الناتجة from this instrument can have significant implications for curriculum development. Educators can use the results to design targeted interventions that address gaps in AI literacy. For example, if students show low understanding of AI concepts, additional instructional support can be provided. Similarly, low scores in ethical dimensions may indicate the need for awareness programs. The data can also inform policy decisions related to technology integration in education. By aligning curriculum with AI literacy competencies, institutions can enhance learning outcomes. This makes the instrument a valuable tool for educational planning and evaluation. (Yue, M., Jong, M. S. Y., Dai, Y., & Lau, W. W. F., 2025)

Furthermore, the implementation of this instrument can support ongoing research in the field of AI education. Researchers can use it to explore relationships between AI literacy and other variables כגון academic performance or motivation. Longitudinal studies can also be conducted to track changes in students’ competencies over time. This contributes to the development of evidence-based practices in education. The instrument can be adapted for different الثقافات and contexts, مما يزيد من قيمته البحثية. By providing a standardized measurement framework, it facilitates comparative studies. Thus, it plays a significant role in advancing scholarly understanding of AI literacy.

In conclusion, the AI Literacy Instrument Grid provides a comprehensive and structured approach to assessing students’ competencies in interacting with AI. It encompasses multiple dimensions, including recognition, understanding, application, evaluation, creation, and ethics. The use of a Likert scale and descriptive quantitative analysis ensures reliable and interpretable results. The instrument not only measures technical skills but also promotes critical thinking and ethical awareness. Its adaptability and practical relevance make it suitable for diverse educational contexts. By equipping students with essential AI literacy skills, it prepares them for the challenges of the digital age. Ultimately, this framework contributes to the development of competent, creative, and responsible users of AI in education. (Gökçe, H., Nacaroğlu, O., 2026)

The questionnaire used a Likert scale of 1 to 4 to assess students' ability levels for each item. Data from the questionnaire were analyzed using descriptive quantitative methods. The score for each item was averaged to determine students' abilities in the five AI dimensions: recognizing, understanding, using, evaluating, and creating. The results of this analysis were used to assess the extent to which students can utilize AI effectively, creatively, and ethically in learning activities. (Yim, I.H.Y., Su, J., 2025)

TABLE 2. AI Literacy Validity

Note:

V = Valid *Significant at p=0.05 **Significant at p=0.01

Based on the expert validity results conducted through the Vexp value, all indicators—Recognizing AI, Understanding AI, Function/Use Apply AI, Evaluate and Create AI, and AI Ethics—met the validity criteria. This is evidenced by the Vexp value for each indicator being > 0.83 according to Aiken's V

criteria, thus theoretically appropriate and deemed feasible for empirical testing by the experts. Furthermore, the results of the empirical validity test using product-moment correlation analysis indicated that all instrument items were declared valid. This is evidenced by the correlation coefficient (r calculated) for each item being greater than the r table value at the specified significance level. These findings prove that all statements in the instrument indeed measure AI literacy according to the established indicators (Yue, M., Jong, M. S. Y., Dai, Y., & Lau, W. W. F., 2025). Thus, empirically, the developed AI literacy instrument meets the validity criteria and is feasible for use in the research data collection phase. This result also strengthens the previous expert validity findings, so the instrument used has a strong theoretical and empirical basis.

TABLE 3. AI Literacy Reliability