Literacy is an essential element of our world. What literacy involves is constantly expanding, and, in the world of education, pedagogies surrounding literacy have shifted to keep up with new theories, techniques, and technology. The introduction of Generative AI has marked a historical turning point when it comes to teaching literacy. In order to understand the impact of Generative AI, however, it is important to briefly examine the history of literacy and how it has changed over time. In the beginning, the language of indigenous cultures was “profoundly multimodal” (Kalantzis and Cope, 2024). Language took on different forms. It was not until 5,000 years ago that writing became what we know it today: “regularized systems of repeatable, symbolic graphemes” (Kalantzis and Cope, 2024). The next stage in history introduced new technologies such as the printing press which exacerbated an “us vs. them” attitude, as illiteracy was used to exclude those of lower classes or minority populations. “Literacy served to draw a line of social division, creating a dividing line between the literate ruling class and the illiterate masses” (Kalantzis and Cope, 2024). In its beginnings, literacy was used as a source of inequality among populations. In the nineteenth and twentieth centuries, literacy became a “social objective” which was encouraged by “mass-institutionalized education” (Kalantzis and Cope, 2024). This meant that inequality now had a basis in the opportunities that were presented to learners which was proven by the “unequal distribution of educational outcomes” (Kalantzis and Cope, 2024). Since this point in time, aspects of literacy have shifted and technologies have grown quickly. This history brings us directly to the introduction of Artificial Intelligence (AI), specifically Generative AI. There is much to explore about this technology including the ways in which it might contribute to the historical trend of inequality, however it might also offer a bright future. With the ever-changing education system and a greater emphasis on the individuality of student learning, the use of Generative AI has allowed for opportunities to learn and practice critical thinking, problem-solving and digital literacy skills in a way that compliments other learning activities. This paper offers an analysis of the educational theories behind Generative AI and how the pedagogy of literacy has shifted with the advancement toward a digital world.

The research questions of this paper are as follows:

1. What are the educational theories connected to the use of Generative AI?
2. What are the critiques of the educational theories connected to the use of Generative AI?
3. How have Generative AI tools been utilized in classroom settings where literacy, specifically writing and digital literacy skills are being practiced?
4. What are the critiques of some Generative AI tools and their uses in classroom settings?
5. How has the pedagogy of literacy shifted as a result of Generative AI?

Personal Motivation

My personal knowledge of Generative AI is minimal. Learners of all grades are aware of Generative AI’s presence and its uses in the world. I feel that it remains attractive to learners as it offers the ability to remove the “thinking” behind a task. This is the main reason for my hesitation to use it in my own classroom. My limited knowledge also adds to my hesitation. I do, however, understand that AI is something that is here to stay and while I may be uncomfortable implementing it, I do recognize that it is important to teach students how to use Generative AI tools in a way that will allow them to continue to practice critical thinking, digital literacy, and problem-solving skills. I was drawn to this topic as I am an eighth-grade social studies teacher and my students are curious about Generative AI. I hoped to better understand how to implement it in my classroom in appropriate ways as much as possible so that students walk away with important knowledge and skills to help them be successful in future endeavors where Generative AI may be prominent.

Constructivism

When it comes to pedagogical strategies, there are three educational theories aligned with Generative AI. A theory of brain developmentalism known as constructivism is the first. Jean Piaget believed that a child’s mental capacity grows through four main stages of development which include: “sensorimotor or pre-language, pre-operational language and thought, concrete operations or logical thought and multiple perspectives and formal or propositional operations embodied in abstract reasoning” (Kalantzis and Cope, 2012). According to the constructivist theory, the learner is responsible for their own growth and constructing knowledge on their own. This only occurs, however, “once a learner’s brain has developed to a certain stage of ‘readiness’" (Kalantzis and Cope, 2012). In this case, learners figure things out on their own through two processes known as assimilation and accommodation, which allow them to take in and build knowledge based on their surroundings. This is completed by "actively working backward and forwards between the two mental processes of accommodation (taking on board new things as they experience them) and assimilation (making sense of new experiences in terms of what they know already)" (Kalantzis and Cope, 2012). The figure below allows for a visual representation of how these processes work. A child sees a four-legged animal known as a dog for the first time. The child has a four-legged pet that is called a dog. The child then calls this four-legged animal a dog. This new knowledge then goes through the accommodation process in that the child realizes that other animals with four legs exist and not all of them are dogs.

Fig. 1: Main, P. (2023). Assimilation vs. Accommodation. https://www.structural-learning.com/post/assimilation-vs-accommodation

Constructivism proposes that "the learner’s mind will only achieve a new stage of development if, when they are ready, they construct that particular understanding of the world on the basis of their developing mental capacities" (Kalantzis and Cope, 2012). Each stage of development offers learners an opportunity to advance their knowledge in different ways and practice essential skills. Although learning conditions differ around the world, Piaget believed that "stages of self-development of human potentiality on the part of the child were universal and thus fundamentally the same" (Kalantzis and Cope, 2012). In the classroom setting, teachers "may set out to create experiential learning opportunities in which students can self-activate or construct mental operations and knowledge on the basis of their natural capacities at a certain age or stage in their development" (Kalantzis and Cope, 2012). Although constructivism is not a new theory, it is closely connected to the emergence of a digital learning environment especially as more technologies have been introduced. Educators have shifted their instruction to intertwine this theory with enhancements in technology, such as the introduction of Generative AI. 

The following video explains how Generative AI works. It explains that new content created by Artificial Intelligence(AI) is called Generative AI. The content is created after a prompt is created explaining the desired outcome. The goal is to provide diverse answers quickly based on data that is then analyzed in order to patterns or similarities. It also addresses how Generative AI can be used in inappropriate ways, to provide artificial responses such as images.

Video 1: KI-Campus. (2023). Generative AI explained in 2 minutes [Video]. YouTube. https://www.youtube.com/watch?v=rwF-X5STYks

A primary example of how educators have implemented Generative AI tools in their classrooms while also practicing constructivism is using Chat GPT to provide feedback. Formative feedback is an important part of growing as a learner but is also time-consuming for educators as providing feedback that is meaningful and allows students to grow takes effort. "One powerful area of potential is in leveraging GenAI tools, specifically ChatGPT, to mentor students by providing formative feedback on student writing and student learning" (Baidoo-Anu & Owusu Ansah, 2023). Especially for online learners who utilize Generative AI tools to construct their own knowledge, feedback is still an important part of learning. Providing meaningful feedback takes a long time for instructors and poses challenges, however, "formative feedback has been demonstrated as an essential component of learner growth" (Uribe and Vaughn, 2017). "Technology-enhanced formative assessment, provided through ChatGPT, can support learners in catalyzing the development of knowledge, providing students the opportunity for immediate, dialogic, and frequent feedback" (McGuire et al., 2024). Especially for online students, using online tools like Chat GPT can give learners instantaneous and meaningful feedback. This will allow students to adjust their learning experiences while continuing to construct their own knowledge at their own pace. Incorporating Generative AI tools into learning environments is important in "helping students develop 21st century digital literacy skills" (Anson, 2022; Bozkurt, 2023). However, while this tool can be helpful for many students, not all learners are aware of the possibilities that Generative AI tools have to offer which contributes to the continued cycle of inequality mentioned earlier.

The following images provide examples for student awareness and use of Generative AI, specifically Chat GPT. The first chart demonstrates student opinions when it comes to appropriate uses of Chat GPT for research and writing essays. Most say it is acceptable to research, some say it is acceptable to solve math problems and few say it is acceptable to write essays. The second chart shows how many teens have used Chat GPT for homework. 19% of U.S. teens ages 13-17 have used it for homework. The third chart shows how awareness of Chat GPT differs among race, ethnicity, and socio-economic status. Awareness of Chat GPT among white students is higher than among students of color and Hispanic students. Awareness of Chat GPT is lower in low-income households compared to high-income households. This information is especially important when discussing practical uses of Generative AI and how this differs in diverse settings.

Fig. 2: Sidoti, O., & Gottfried, J. (2023). About 1 in 5 U.S. teens who’ve heard of ChatGPT have used it for schoolwork. https://www.pewresearch.org/short-reads/2023/11/16/about-1-in-5-us-teens-whove-heard-of-chatgpt-have-used-it-for-schoolwork/

Fig. 3: Sidoti, O., & Gottfried, J. (2023). About 1 in 5 U.S. teens who’ve heard of ChatGPT have used it for schoolwork. https://www.pewresearch.org/short-reads/2023/11/16/about-1-in-5-us-teens-whove-heard-of-chatgpt-have-used-it-for-schoolwork/

Fig. 4: Sidoti, O., & Gottfried, J. (2023). About 1 in 5 U.S. teens who’ve heard of ChatGPT have used it for schoolwork. https://www.pewresearch.org/short-reads/2023/11/16/about-1-in-5-us-teens-whove-heard-of-chatgpt-have-used-it-for-schoolwork/

The following external link is another example of how students can use AI at home for immediate feedback. Khanmigo is a Generative AI tool from Khan Academy that allows learners to get homework help and write papers. It also provides learners with essential feedback.

https://www.khanmigo.ai/

Source: Khanmigo AI, Khan Academy’s AI-Powered Teaching Assistant & Tutor. https://www.khanmigo.ai/

Behaviorism

The next theory associated with Generative AI is behaviorism, which was founded by John B. Watson, Edward Thorndike, and B.F. Skinner. Their research centered around the idea that "the only thing we can know with any degree of certainty in the science of psychology is what we can see in the form of observable behaviours" (Kalantzis and Cope, 2012). This greatly differs from constructivism as behaviorists argued that “thinking about thinking” was not necessary and that spending time reflecting on the nature of the mind had no meaningful use (Kalantzis and Cope, 2012). A central idea of behaviorist research is that learning is “conditioned by stimuli" (Kalantzis and Cope, 2012). The stimuli "may take the form of negative reinforcement (pain, punishment) or positive reinforcement (pleasure, reward)" (Kalantzis and Cope, 2012). B.F. Skinner led the way in this research with what is known as “Skinner boxes.” An animal was placed in a box and then received a stimulus. Depending on the response, they were rewarded or punished. Skinner’s findings argued that both animals and humans were the same. The diagram below provides an image of how these worked. The animal, in this case, a rat, would be placed inside a box. When the rat performed a desired response, it would receive food through the pellet dispenser. When the rat performed an undesired response, it received an electrical shock through the grid or a loud noise through the speaker.

Fig. 5: Britannica. (n.d.). Skinner Box. https://www.britannica.com/biography/B-F-Skinner

In terms of education and how this transfers to pedagogy, classroom teachers are responsible for creating environments that promote optimal learning, "Stimulus takes the form of teacher and textbook exegesis of curriculum content." (Kalantzis and Cope, 2012). The responses then take on various forms such as assessments or grades. This form of instruction is known as didactic and is more traditional than what contrasting theories promote. The teacher provides the stimulus for learning and the responses are given in the forms of positive and negative reinforcement which in the classroom setting is equivalent to “A’s” or “F’s” (Kalantzis and Cope, 2012). The essential difference between behaviorism and constructivism is that learning can be controlled by external stimuli or learning can be constructed independently by learners. Along with constructivism, behaviorism is not a new theory, yet educators have incorporated technology into their behaviorist instruction. The behaviorist theory demonstrates strong connections with Generative AI. By incorporating technological tools within a classroom setting, educators can control the stimuli that students are interacting with, also controlling the outcomes and conditions while at the same time presenting students with the knowledge they need and introducing new experiences and activities. "With educational technology as an approach or as a tool, it is a behaviorism approach by stimulating students through psychological conditions because, through the educational technology tools, the educator can stimulate learners by direct experiences and activities inside the class" (Standridge, 2002). This technology “supports good behavior and changes bad behavior” (Buhamad, 2024). With the educator having more control over the stimuli presented, students are encouraged to learn more by the presented conditions and stimuli which corresponds with B.F. Skinner’s research suggested humans would repeat the same action so long as there was a favorable outcome "The result of psychologists B.F. Skinner’s research shows that both humans and animals would do the same action if they got the same favorable outcome, and they would prevent the action that led them to the unfavorable result" (Standridge, 2002). In this case, it is all up to the instructor to determine which activities would be appropriate to stimulate student growth and response. "The purpose of using educational technology is that it has a lot of functions that help the educator make a link between the knowledge and the symbol or the content" (Buhamad, 2024). While observing the behaviorist theory and the incorporation of technology in action, it was found that "mixing the instructional technology with behavioral theory provided perfect tools that achieve the target of the responses of stimuli" (Buhamad, 2024).

Connectivism

The third theory connected to Generative AI is connectivism which recently emerged due to the result of a trend toward learning in a digital world. The emergence of this theory indicates the dramatic shift in pedagogy due to online learning and Generative AI tools. Connectivism is directly associated with Generative AI tools as learning in this theory is completed almost entirely through the use of online or technological materials. Connectivism is different than any other learning theory in that it "attributes learning through cyber nodes specifically rooted in social networks" (Kropf, 2023). According to this theory, learners gather information through "modern-day reservoirs of information" (Kropf, 2023). There are currently three reservoirs where learners get information. The infographic below provides a visual representation of the three reservoirs.

Fig. 6: Information Reservoirs. (Kropf, 2023 pg. 15).

The three reservoirs shown above are "(a) online classrooms including massive open online courses (MOOCs), (b) social networks including podcasts and video clips, and (c) virtual reality platforms, including ‘Second Life’ and 3-dimensional video games" (Kropf, 2013). The internet is the main source of learning in this theory, therefore Generative AI tools are becoming an essential element of connectivism. The eight principles of the connectivism learning theory presented by George Siemens (2005) in Connectivism: A Learning Theory for the Digital Age are as follows:

1. Learning and knowledge rests in a diversity of opinions.
2. Learning is a process of connecting specialized nodes or information sources.
3. Learning may reside in non-human appliances.
4. Capacity to know more is more critical than what is currently known.
5. Nurturing and maintaining connections is needed to facilitate continual learning.
6. Ability to see connections between fields, ideas, and concepts is a core skill.
7. Currency (accurate, up-to-date knowledge) is the intent of all connectivist learning activities.
8. Decision-making is itself a learning process. Choosing what to learn and the meaning of incoming information is seen through the lens of a shifting reality. While there is a right answer now, it may be wrong tomorrow due to alterations in the information climate affecting the decision.

Connectivism is relevant when discussing Generative AI tools such as Chat GPT as these are "nodes" by which learners gather information. Learning, according to connectivism, is described as "an informal opportunity that transforms individuals into ‘nodes’ themselves, equally capable of sharing their knowledge and expertise with other individuals" (Kropf, 2013). In the connectivist theory, a guiding principle is "how higher order thinking skills are activated when individuals can distinguish which of the abundant and diverse information available online are reliable or sustainable" (Kropf, 2013). The connectivist theory allows online learners to connect with one another and learn from each other in an independent way. This allows learners to practice critical thinking and problem-solving skills with others while working through online learning materials. This theory provides educators with a way to incorporate technology into their classrooms while also allowing students to continue practicing transferable skills.

Critics of Educational Theories

It should be noted that educators often use the aforementioned theories interchangeably. There is no one "perfect" educational theory that all educators use. The style of teaching and theory or theories used is entirely dependent on the personality of the teacher and the needs of the students in their classes and teachers may shift between using all or none. While these educational theories offer different ways of instruction and have allowed pedagogy to either expand or narrow over time, there are critics. Educators have utilized the constructivist theory in their classrooms in an exploratory way, allowing students to derive their own meaning from many topics rather than using the traditional behaviorist approach that emphasizes didactic instruction. Critics of the constructivist theory argue that this style of teaching is unguided, providing little meaningful instructions that students need to follow when completing learning activities (Alanazi, 2016). When it comes to Generative AI, students may not learn how to use it in an appropriate way or understand all that it has to offer if there are no guided learning activities. Critics also argue that this approach may lead students to feel frustrated as minimal guidance devalues structure and does not allow students to enhance their working memory skills (Alanazi, 2016). Another concern is that learners need to connect their knowledge in a hands-on way and some argue that the constructivist theory does not necessarily take this into account (Alanazi, 2016). For example, if a learning outcome is for students to design a webpage using HTML, constructivists may have students learn through collaboration and problem-solving with their peers, not necessarily creating a webpage on their own (Alanazi, 2016). Critics argue that if students can accurately connect knowledge to a tangible outcome, then knowledge is constructed in the correct way.

When it comes to behaviorism, which is considered to be a more traditional approach to learning and teaching, critics consider behaviorism to be "a one-dimensional approach to behavior" (Rostami and Khadjooi, 2010). Critics also argue that "behaviorism can not be applied to learning if there is no punishment or reinforcement" (Rostami and Khadjooi, 2010). Another argument against behaviorism is that it "cannot account for all types of learning since it disregards mind activity" (Rostami and Khadjooi, 2010). With educators placing more emphasis on the individuality of the learning needs of each student, this theory may not be as relevant. Every individual is unique and the reason learners react to something the way that they do goes well beyond the time of stimuli that is placed in front of them. Another critique is that "some situations do not have a correct response which leaves the learner unable to respond" (Rostami and Khadjooi, 2010). While behaviorism may be useful to educators who believe that using positive and negative reinforcement is the only means to educate, it has lost much of its appeal due to constructivism and other modern theories of education. 

Critics of connectivism argue that rather than a learning theory, it is an instructional theory. "An instructional theory is a conceptual framework based on empirical findings and grounded in learning theories, which recommends the design of learning materials, resources, or situations to help learners achieve their learning outcomes and maximize their learning potential" (Kropf, 2013). Some critics suggest that researchers need to "reassess the promises of online education and the connectivism or network learning that is sometimes employed as its pedagogical underpinning" (Dennis, 2020). Some critics also argue that "connectivism lacks a substantive theoretical foundation, others contend that connectivism is actually the latest development of constructivism" (Dennis, 2020). When it comes to higher education online learning specifically, critics argue that "asynchronous interactions are not engaging and rigorous enough for higher education" and that "virtual environments are not able to provide students with the same quality and caliber of education that traditional, face-to-face courses can" (Reese, 2015). Another common concern is the sub-standard of work that can be the outcome of online learning environments. 

Behaviorism and Technology

There are multiple examples of how the theories mentioned above can be practically applied in the classroom, especially while utilizing technology. The following case studies demonstrate a shift in pedagogy as education becomes more digitally focused. The first case study focuses specifically on the behaviorist and constructivist theories and how different classroom settings have blended these theories with technology. The participants in this study were two college instructors, and 10 college students. They were all volunteers. All the participants had experience teaching. The data collection methods were observation, interview, and document analysis. When the theory of behaviorism was observed, "the following tools of educational technology were used: some pictures of crystalline metals, an instructional video showing how halite is established, a model of the spatial structure of the crystal, electronic tables to determine and compare the differences between the properties of the crystals, and a PowerPoint presentation to support knowledge by simulation" (Buhamad, 2024). In the behavioral classroom setting, "the teacher started to explain the content by using the direct experiences of the teacher mixed with instructional videos and electronic tables to determine and compare the differences between the properties of the crystals" (Buhamad, 2024). The teacher "gave an opportunity for the students to change some numbers in electronic tables to see the result of this effect, supported by pictures to explain the factors that affect crystalline metals" (Buhamad, 2024). The teacher repeated this multiple times with other modes of technology. Just like Skinner's study, the learner repeated the action that helped them achieve a positive result.

Constructivism and Technology

The constructivist theory was next to be observed. In this case, an instructor of photography was explicitly asked to use this theory to teach content. The lesson was structured as an inquiry-based lesson as the instructor began the lesson by posing a question "to analyze and understand the student’s previous knowledge about photography" (Buhamad, 2024). "The following tools of educational technology were used: some of his high-quality pictures as examples, a funny story supported by an instructional video to get their attention, a real camera with all necessary equipment to the classroom to practice with, and a PowerPoint presentation to support the knowledge by simulation" (Buhamad, 2024). The teacher offered background information and generated a class discussion. Students were given the ability to practice in a real environment and then were able to share their photos with the class "to discuss them as a group to evaluate them and give feedback" (Buhamad, 2024). The instructor then created a "constructivist environment to give them more clarification and more opportunity to discover more about the photography they want to create by using PowerPoint slides that include the content and more pictures, video, and text" (Buhamad, 2024). The PowerPoint slides had challenging words and a link to websites that students could explore if they chose to. The final slides included a self-assessment for students. In this case study, students were given the opportunity to construct their own knowledge using technology.

Generative AI and Literacy at the University Level

In the case of Generative AI, more specifically Chat GPT, educators have utilized this technology in various ways in differing contexts. The next case study addresses a specific use of Chat GPT in the classroom. Shu Wan, a doctoral student at the University of Buffalo observed one of her students asking Chat GPT to help them write an assignment for her course. She became motivated to create an instructional section that helped refine students’ skills in literacy. While preparing for the section, Shu Wan became frustrated with the generated questions Chat GPT gave her, especially when it came to female figures in China. The generated information failed to highlight necessary information that was historically important to the females and instead provided information praising the females as wives and mothers. She became worried about the influence Chat GPT had over her students and how often they were using it, leading to an intake of biased information. Shu Wan decided to create an informative literacy session alongside an interactive writing assignment. Instruction began with lectures on the prejudice and social justice that are intertwined with Chat GPT. After the introduction, students were assigned to read a book about female figures in Chinese history. When students completed the readings, students were tasked with two objectives: “1) ask ChatGPT to evaluate the selected figures; and 2) contrast the rhetorical difference in the machines’ and historians' opinions (in the class reading) on them” (Shu Wan, 2024). As students compared and contrasted the information that was generated about the political figures, students were encouraged to collaborate through conversation about the differences in how Generative AI depicts men and women (Shu Wan, 2024). Students were then asked to reflect on their findings using Padlet and review the work that their classmates had posted. This allowed students to examine the use of Chat GPT with a different perspective. After concluding the study, Shu Wan hopes that library workers will be inspired to teach about information literacy. The outcome of the study provides an example of a limitation of Chap GPT, specifically the bias surrounding gender, race, and other factors. This outcome urges educators to remain cautious while also continuing to inform students of how to use Generative AI.

Using Generative AI in English as Foreign Language Classrooms

The next case study analyzes the impact of writing tools on the content and organization of student writing. This study specifically focused on insights from English as Foreign Language (EFL) teachers as to how the quality of student writing was impacted due to Generative AI. There were four writing teachers chosen for this study from varying institutions. The teachers were chosen based on “practical experience with AI writing tools in the classroom, accessibility, willingness to participate, and teaching expertise in advanced courses such as essay writing and argumentative essay” (Marzuki et al., 2023). The teachers had at least three years of experience teaching writing courses and at least one-year utilizing Generative AI tools in their classes. The AI tools were “supplementary teaching resources, aiding in grammar checking, paraphrasing, plagiarism detection, generating content, and offering suggestions to enhance the clarity and coherence of students’ writing” (Marzuki et al., 2023). The setting where each participant taught varied in size to allow for the diversification of factors that may influence the outcome of how AI tools were utilized. Interviews were used as the data collection point as well as literature reviews to ensure that the questions asked relied on recent research. Literature used included “works by Nazari et al. (2021), Dale and Viethen (2021), M. Leeet al. (2022), and Zhao (2022)” (Marzuki et al., 2023). Some questions asked included “What AI writing tools have you used in your classroom?” and “In what ways have these tools impacted your students’ writing, specifically with respect to content and organization?” (Marzuki et al., 2023).

The results of the study showed that the participants each used various types of AI tools that were chosen in particular to meet the needs of their differing learning environments. Each teacher used multiple tools with different purposes. Some of the AI tools include Chat GPT, Wordtune, Essay Writer, Quillbot, and Jenni AI. Quillbot and Wordtune were used by all teachers. After conducting interviews with the participants, each provided vital feedback for the researchers. One response was as follows:

“AI writing tools have been instrumental in boosting students’ creativity by providing suggestions and expanding on initial ideas. When students get stuck or encounter writer’s block, these tools can propose different angles or perspectives, assisting them in overcoming creative hurdles” (Marzuki et al., 2023).

Another contrasting response was:

“In my experience, AI writing tools have had mixed effects on students’ abilities to generate ideas. On one hand, they can provide a starting point when a student struggles with idea generation. However, the ideas generated by the tool can be rather generic or lack personal touch. Therefore, while they can be helpful in some instances, they might not always encourage students to think deeply or critically about a topic” (Marzuki et al., 2023).

Another contrasting response to the above reviews was:

“I’ve observed that AI writing tools can sometimes inhibit students’ ability to generate original ideas. This might be because they become reliant on the tool’s suggestions, and stop pushing themselves to think outside of the box. In some cases, it might be more beneficial for students to struggle with idea generation and problem-solving, as these are valuable skills that can be cultivated through practice” (Marzuki et al., 2023).

In conclusion, all four participants agreed when it came to the benefits of AI tools when it came to “enhancing the clarity and logical progression of students’ writing” (Marzuiki et al., 2023). The participants also raised concerns about the reliance on AI writing tools which could harm students when it comes to essential critical thinking and problem-solving skills. The outcome of the study does suggest overall that using AI writing tools can enhance the quality of EFL writing.

Connectivism and Digital Literacy Skill Practice

In this final case study discussion, ideas for how to utilize the theory of connectivism are addressed. For example, the first guiding principle, "learning and knowledge rests in diversity of opinions," Wikipedia-based assignments may be created and it is a direct example of this principle. "Wikipedia and entry-writing exercises are becoming more common on college campuses as academia and the online site drop mutual suspicions and seek to cooperate" (Utecht and Keller, 2019). Principal number 4, "capacity to know more is more critical than what is currently known," is important for learners but it is necessary to teach guidelines. "In a knowledge economy, the capacity to learn, unlearn, and relearn quickly is another core skill" (Utecht and Keller, 2019). Students have access to the world at their fingertips and excel at finding information, however, one raised concern is that "there is a lack of skill to find the information and validate it" (Utecht and Keller, 2019). Teaching this skill may look like introducing students to databases and instructing them where to find accurate and reliable information that offers new perspectives. For example, "doing a search for “American War site:gov.vn,” students are instantly taken to a different perspective of this conflict, a perspective that very few Americans have ever studied or thought about" (Utecht and Keller, 2019). It is a simple fix that allows students to enhance their digital literacy skills. Lastly, principal number 7, "currency (accurate, up-to-date knowledge) is the intent of all connectivist learning activities," is an important skill to teach learners. The internet provides new information daily, so teaching students how to use search engine settings to filter through all of this information allows them to find the latest and most updated news. Helping students to use the "ctrl + F" feature also helps students narrow down what they are looking for. These simple fixes also allow students to improve their digital literacy skills.

The Evolution of Technology

In order to fully understand how the pedagogy of literacy has changed over time, it is important to discuss how classrooms have changed due to the evolution of technology. Pre-1800 classroom learning was focused on the individual. "The standard practice was for the village schoolmaster to call one or several pupils to his desk, and teach individually" (Turkmen, 2006). It was not until Joseph Lancaster introduced his "Lancasterian monitorial system" that "large-group instruction started and classrooms were constructed that would make the most effective use of instructional media and student grouping" (Turkmen, 2006). Teaching was often lecture-based, with chalkboards located at the front of the room. As technological inventions were introduced into the educational setting, schools adapted and expanded their opportunities for learners. Electricity was one of the most impactful innovations for teachers as it allowed learning to occur in more environments. "By the 1950s, photography, photojournalism, sound motion pictures, and broad radio firmly established American educational traditions" (Turkmen, 2006). These technologies became an integral part of the education system as they were often used to promote positive propaganda about American education. The next major invention was the printing press, followed by the television. This led to the use of overhead projectors in classrooms. "By 1970s, science teachers began to use the overhead projector, which shows diagrams, charts, or figures that clearly indicate analysis of the topic, pictures" (Turkmen, 2006). This takes us directly to the invention of the computer which was able to "enter the classroom after the 1980’s" (Turkmen, 2006). The incorporation of the computer led to the internet which transitioned to the myriad of technological tools we have today, including Generative AI. Educators have historically kept up with the demands that new technology has brought, including how to use it in positive ways while also teaching students how to use it appropriately. The case studies above add to this history and demonstrate just how much pedagogy has changed with the introduction of Generative AI. 

Connections to Educational Theories

The case studies mentioned above provide examples of how Generative AI tools can be used in the classroom setting, especially in correspondence with the behaviorist, constructivist, and connectivist theories of education. They also demonstrate how educators have shifted their pedagogy of writing and digital literacy to incorporate technology in their classrooms. The university-level practical example of using Chat GPT in the classroom utilizes both the constructivist and behaviorist theories. By creating the stimuli students responded with including the lectures, books and digital tools, the teacher manipulated the learning environment and controlled the learning outcome which aligns with the behaviorist theory. By allowing students to have choices and to collaborate with one another while also providing feedback aligns with the constructivist theory. This was a clear example of how to use both theories while also allowing students to create their own conceptions about Generative AI. There are multiple limitations of this study. This includes the inherent bias against Chat GPT that already existed, the size of the student population involved as well as the backgrounds of all of the students involved. The students were all at the college level and taking a course in the specific content area that was involved in the study. This specific case fulfills the promise of both the behaviorist and constructivist theories as the teacher controls stimuli while also allowing students to construct and develop their own knowledge. This case study was especially interesting as it was designed due to a concern over Chat GPT. It turned out to be an eye-opening and informative piece of research, especially for educators at the post-secondary level. While both aforementioned theories of education were utilized, it also provided an example of how to use Generative AI tools as a secondary learning activity that still allowed students to collaborate with one another and address their own learning.

The practical example that took place in English as Foreign Language (EFL) classrooms is aligned with the behaviorist theory of education as the teachers were controlling the stimuli used in their classrooms. It also aligns with the constructivist theory as the students were practicing how to use each of the AI writing tools independently as well as the connectivist theory because students were using online Generative AI tools. Because multiple tools were used, this means that students were able to explore and construct knowledge as to how they could appropriately use all of them and what each allowed them to do. Limitations of the study include participant selection as each teacher was already using the AI writing tools mentioned above and already had a bias towards them as they were actively encouraging their use. It was suggested that in the future, participants who try out tools to decide whether or not they want to continue using them should be chosen in order to broaden their perspective and better address any barriers (Marzuki et al., 2023). This particular case study was another example that fulfilled both constructivist and behaviorist theories of education. It demonstrated ways that Generative AI can again be used as a secondary learning activity. The results of both of these case studies prove that Generative AI tools are best when used alongside other learning opportunities, but that they should not be used as the only way to learn and engage in different content-based activities. These practical application examples prove how educators have shifted their pedagogical ideologies and methods to better incorporate technological tools that benefit students.

Practical Applications

The case studies above offer various examples of practical applications of Generative AI tools in classroom settings. Generative AI tools such as Chat GPT, Wordtune, Essay Writer, Quillbot, and Jenni AI can help teachers assist in the student writing process. These tools help with the organization, structure, and grammar of writing. These tools offer various opportunities for learners such as spelling correction, plagiarism protection, and paraphrasing help which could be especially useful in situations with students who speak other languages. When it comes to specific Generative AI tools, Chat GPT can be used to practice and enhance critical thinking and problem-solving skills. By using Chat GPT as a secondary resource to compare and contrast writing or sources of information, learners can identify where to find factual, relevant information while also getting help with the structure of their writing. This is a great tool that can be used to enhance digital literacy skills as learners will be able to recognize AI bias and discover how it can help them in research and writing assignments. Websites like Wikipedia provide a collaborative learning environment where students can learn from each other while also contributing to information that may be included on the website. Other more simple actions such as showing students how to narrow down search requests to find the most up-to-date and meaningful information can also contribute to digital literacy practice. Introducing students to databases and instructing them where to find accurate and reliable information that offers new perspectives allows them to continue building their critical thinking and problem-solving skills. Using AI in the classroom as much as possible and showing students how to use it to appropriately assist them in their work while still allowing them to practice essential skills and do most of the thinking will greatly benefit students.

Online Learning Environments

In the world of education, a major shift of pedagogy revolves around the use of online learning environments. With an increase in digital technology and a greater focus on incorporating technological tools in the classroom, it is important to address critics, especially critics of online learning environments. In this case, critics respond to the increased presence of online educational opportunities at the college level. Critics of online learning environments suggest that there is a "dissociative process that can accompany virtual learning environments, and acknowledge a disconnect in the instructor and student relationship, as well as in the ability to build a learning community" (Reese, 2014). The connectivism theory offers alternative ideas for online learners to stay connected with each other, however, a concern is the "lack of interaction within a specific building in a set time and place as a negative aspect of online learning" (Reese, 2014). Although there has been a significant increase in online classes, some argue that these environments are "not able to provide students with the same quality and caliber of education that traditional, face-to-face courses can" (Reese, 2014). Because online learning removes the in-person dialogue between instructors and students, this creates another concern in that "communication and dialogue between students and instructors is missing from distance education" (Reese, 2014). While there are a myriad of concerns that arise with online environments, they are not going away. Online programs should be conducted in ways that allow learners to remain connected with their instructors, collaborate with one another, and that challenge students.

Online Learning Environments: A Response to the Critics

While critics of online learning and Generative AI remain, AI has been proven to be effective in improving instruction and student outcomes. Information and Communication Technologies (ICT), have become a part of our world in recent decades. "The various kinds of ICT products available having relevance to education and serving different purposes, include teleconferencing, email, audio conferencing, television lessons, radio broadcasts, interactive radio counseling, interactive voice response system, group text messaging, group audio messaging, file transferring, learning apps, etc." (Dutta and Nessa, 2022). The technologies available to educators have transformed the learning space and allowed students from all over the world to learn from and connect with one another. Online learning environments have contributed to a "break in the physical barriers to training and encouraged interacting in a completely new and different way" (Dutta and Nessa, 2022). For students who struggle with traditional education practices, online learning can be beneficial.

Generative AI and Ethics

While focusing on Generative AI, specifically the use of Chat GPT, it is necessary to examine critics of this technological tool. In a study by Mittal et al. (2024), Comprehensive Review on Generative AI for Education, concerns regarding Generative AI tools are addressed. These concerns involve copyright, inability to control the outcome, privacy, security and ethics, training and maintenance, bias and fairness, and the ability to distinguish responses between the model and students. In the world of education, with an increasing number of assessments transitioning to online settings and student access to AI tools, privacy, security, and ethics are major concerns. However, the study also provides countermeasures to these concerns such as utilizing GPTZero which can detect AI responses versus student responses, the inclusion of diverse datasets, and incorporating AI methods that are easy to explain. Debates over the use of Generative AI tools are increasing, especially due to ethical concerns, specifically academic dishonesty. "Overdependence on chatbots like ChatGPT is widely considered detrimental to students’ development" (Ngo et al., 2024). Plagiarism introduces various risks when it comes to academics. Students not only lose out on practicing critical thinking and problem-solving skills, but the information they take may be biased and inaccurate. In Academic Integrity in the Age of Generative AI: Perceptions and Responses of Vietnamese EFL Teachers, Ngo Cong-Lem, Tin Nghi Tran, & Tat Thang Nguyen (2024) outline their survey results regarding teacher concerns when it comes to an over-reliance on chatbots. Their survey was completed in order to collect data on Vietnamese EFL teachers and their experiences with academic dishonesty due to AI. The chart below demonstrates the outcomes:

Fig. 7: Academic Integrity in the Age of Generative AI. (Ngo et al., 2024 pg. 33)

The chart highlights interesting points. While plagiarism is the top concern, not utilizing citations and a lack of original ideas are areas of academic dishonesty due to the use of AI.

A Critical Discussion of Generative AI Tools

Critics of Generative AI programs, specifically Chat GPT argue that it is not necessarily successful when it comes to teaching critical thinking and problem-solving skills that could lead to a decline in "human connection and individualized learning" (Graefen and Fazal, 2024). The socialization aspect of education is important for students' cognitive growth and development, especially for learners at younger ages. While Chat GPT offers many positives as a teaching tool, educators are tasked with finding appropriate ways to incorporate its use while still emphasizing the importance of individual writing and collaborative skills students will need moving forward. Another argument against Chat GPT is that educators cannot be sure of the accuracy of the content that it provides, which is especially important in certain fields such as medicine which can lead to negative consequences and have "ethical ramifications" (Graefen and Fazal, 2024). "The common use of Chat GPT in academic work has brought up ethical dilemmas concerning AI authorship. Evaluating academic tasks such as students' essays has also raised ethical debate. Plagiarism of content is an inevitable concern that has been discussed, and suggestions have been made to modify essay settings and guidelines to address these issues" (Graefen and Fazal, 2024). This leads to another limitation in that it often fails to discuss how involved Chat GPT is when it comes to many social media platforms which are often biased and may be taken into account in student responses (Graefen and Fazal, 2024). Other critiques of tools like Chat GPT involve enhanced inequalities due to a lack of educational technology available to students and a decrease in "lifelong learning" (Kapil, 2024). While there are a multitude of critiques, developing a framework for when and how to use Generative AI may be helpful, especially within the connectivist context. This would allow students to practice digital literacy skills. The following flowchart is an example of what students could use as it takes them through different scenarios and questions:

Fig. 8: Cheating Better with ChatGPT: A Framework for Teaching Students When to Use ChatGPT and Other Generative AI Bots (Firth et al., 2024 pg. 49)

Teacher Training

In order to help educators feel more comfortable implementing certain Generative AI tools and technology in the classroom while avoiding the aforementioned concerns, teacher training programs need to be improved. "One must be proficient in using a variety of technology tools to solve problems, make informed decisions, and generate new knowledge" (Roab et al., 2012). Educators should be prepared to utilize technology in the classrooms and be made aware of the positives and drawbacks of a wide array of tools. "Teacher education needs to provide instruction that promotes the benefits, modes, and strategies for effective technology integration" (Roab et al., 2012). There are multitudes of Generative AI resources for educators to utilize in their classrooms. By providing deeper instruction into these resources, teachers can feel more confident using them in daily learning activities. In Pre-Service Teachers’ Dual Perspectives on Generative AI: Benefits, Challenges, and Integration into their Teaching and Learning, Bae et. al., (2024) describe the outcomes of a study aimed at defining how comfortable pre-service teachers felt using Generative AI. Based on personal experiences, many of the pre-service teachers were anxious about incorporating Generative AI into their future classrooms. "Despite engaging in weekly discussions about using ChatGPT, which increased their awareness and foundational knowledge of GenAI tools, they primarily focused their conversations on the perceived benefits, concerns, and challenges associated with using ChatGPT" (Bae et al., 2024). These limitations mainly revolved around ethical concerns and the uncertainty of the impact of AI on student outcomes. "To address this challenge, pre-service teachers may benefit from additional professional development opportunities aimed at understanding AI concepts and ethical considerations to reduce uncertainty and enhance familiarity with AI use in educational settings" (Bae et al., 2024). It is understandable why educators feel hesitant, but education is key for increasing the comfort of the use of AI in classrooms.

Personal Thoughts

Throughout my research for the project, I learned how I can incorporate Generative AI into my own classroom with my 8th-grade students. I wanted to learn more about their thoughts on AI and how often they try to utilize it for their school assignments. I began with a survey and asked students the following questions:

1. Have you used AI tools?
2. What tools have you used?
3. What have you used them for?
4. Were the tools helpful to you?
5. Have you used these tools to cheat before?
6. Do you think it would be useful to learn how you can use AI tools to help you with schoolwork?

The majority of my students had used AI tools. The most common tool they used was Chat GPT and they utilized this for both math and science classes to help them solve problems and complete writing responses. Most of my students had not used the tools to cheat in the past, however, some admitted that it was difficult to cheat with AI tools because of the way assessments are distributed. Most students wanted to learn how they could use tools to help them with schoolwork in a productive and meaningful way. Those who responded “no” to that question were afraid the tools would lead them to cheat. The visual responses are as follows:

Fig. 9: Maggie Mancl Classroom Survey

Fig. 10: Maggie Mancl Classroom Survey

Fig. 11: Maggie Mancl Classroom Survey

Fig. 12: Maggie Mancl Classroom Survey

I then created a series of lessons based on the results of the survey to start incorporating the use of Generative AI tools in my class. I began by talking students through some research prompts. I had them just do a broad Google search for answers to begin and then showed them some navigation tools. We then had a discussion of what makes a source a “good” source. I then had students write a response to the following question: How did infrastructure help America expand in the 1800s? After students wrote their own responses, I had them use Chat GPT to generate a response to the same question. Students compared their response to the AI-generated response. I acknowledged with them that the AI response would be much more detailed and probably a higher grade level than their own responses. I wanted my students to see the structure, grammar, and amount of detail that the AI response contained. Many of my students realized that they could grow significantly when it came to their own writing. After looking through the AI responses, they went back and edited their own. I then introduced other Generative AI writing tools that they could use to avoid plagiarizing, check their spelling, and better structure their writing. I plan to continue to introduce more tools as well as model how to use them. Doing this has allowed students to practice digital literacy, critical thinking, and problem-solving skills while also improving their work. By completing this research paper, I feel more comfortable and confident using AI in my classroom.

Research Recommendations

Possible research questions to consider moving forward are as follows.

1. How can different Generative AI tools be used at different grade levels? The use of Generative AI is going to look different at the high school level than it does at the kindergarten level. It would be interesting to look into how Generative AI tools could be used at the kindergarten level, if not by students than by teachers.
2. How has the use of Generative AI improved student work? This research question may take years to answer as AI is relatively new and may not be used in all school settings. However, answering this question would assist educators in how to utilize it in their classrooms.
3. What is the future of Generative AI? Generative AI is only going to grow, looking into this question would allow educators to better prepare for the future and the ever-increasing focus on a digital world.

Concluding Thoughts

The introduction of Generative AI, specifically AI writing tools like Chat GPT has greatly transformed pedagogy and student writing. The constructivist and behaviorist theories of technology have remained part of pedagogy for many years and have become closely linked with Generative AI as it has become more prominent. Educators use the behaviorist theory of education by controlling the stimuli, (in this case Generative AI tools), and manipulating the learning environment which determines what students need to learn. The correct responses are praised through positive reinforcement and the incorrect responses are “punished” through negative reinforcement. Educators also use the constructivist theory of education by allowing students to explore the use of Generative AI tools which helps them to determine for themselves what is important. Critics of both these theories argue against the amount of structure that comes with each theory. Critics of behaviorism argue that it is too structured and takes away the individuality from learners. Critics of constructivism argue that there is too little structure and that using AI tools with this theory will take away from important social interactions. However, the theory of connectivism offers ways to blend educational theories with technology. The introduction of the connectivist theory of education marked a pedagogical turning point in that an entire educational theory revolved around online materials. For example, educators have been utilizing Generative AI tools as secondary components in their classrooms, specifically tools like Chat GPT. The case studies shown above demonstrated both positives of AI use and introduced concerns. AI tools allow for opportunities for immediate feedback and to hone in on certain writing skills. On the other hand, the overuse of Generative AI tools may take away from critical thinking skills and may contribute to inaccurate information that contains bias. Regardless of an educator's opinions about Generative AI, it is growing quickly and will now be a permanent part of pedagogy moving forward. It has become a historical element of the expansion of literacy and it is essential that the educational community focus on how to utilize it in positive ways. Instead of focusing on the cons, educators must teach students how to use Generative AI in an appropriate way so that it can benefit them, rather than hinder their educational opportunities. If we refuse to accept the fate the Generative AI has brought us, literacy will no longer exist in our artificial world.

Abby Mcguire, Warda Qureshi, & Mariam Saad. (2024). A constructivist model for leveraging GenAI tools for individualized, peer-simulated feedback on student writing. International Journal of Technology in Education, 7(2), 326–352. https://doi.org/10.46328/ijte.639

Ali Mahmoud Buhamad. (2024). The application of behavioral and constructivist theories in educational technology. Journal of Education and Learning, 13(3), 52–61. https://doi.org/10.5539/jel.v13n3p52

Alanazi, A. (2016). A critical review of Constructivist theory and the emergence of Constructionism. American Research Journal of Humanities and Social Sciences, 2, 1–8. https://doi.org/10.21694/2378-7031.16018 

Anson, C. M. (2022). AI-based text generation and the social construction of ‘fraudulent authorship’: A revisitation. Composition Studies, 50(1), 37-46.https://doi.org/10.7330/9781646425341.c000a

Bae, H., Park, J., Jaesung, H., Choi, G. W., & Moon, J. (2024). Pre-service teachers’ dual perspectives on generative AI: Benefits, challenges, and integration into their teaching and learning. Online Learning Journal, 28(3), 131-156–156. https://doi-org.proxy2.library.illinois.edu/10.24059/olj.v28i3.4543

Baidoo-Anu, D., & Owusu Ansah, L. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. SSRN. http://dx.doi.org/10.2139/ssrn.4337484 

Bozkurt, A. (2023). Generative artificial intelligence (AI) powered conversational educational agents: The inevitable paradigm shift. Asian Journal of Distance Education, 18(1), 198-204. https://doi.org/10.5281/zenodo.7716416

Dennis, J. (2020). Languaging network learning: The emergence of connectivism in architectonic thought. International Review of Research in Open & Distributed Learning, 21(3), 304–318. https://doi-org.proxy2.library.illinois.edu/10.19173/irrodl.v21i3.4718

Dutta, A., & Nessa, N. (2022). Technological competencies of teachers in teaching-learning processes and the librarians’ role to enhance technological skills: A study. Library Philosophy & Practice, 1–13.

Encyclopædia Britannica. (n.d.). Skinner box [Image]. https://www.britannica.com/biography/B-F-Skinner#/media/1/547663/286870

Firth, D., Derendinger M., & Triche, J. (2024). Cheating better with ChatGPT: A framework for teaching students when to use ChatGPT and other generative AI bots. Information Systems Education Journal, 22(3), 47–60. https://doi.org/10.62273/BZSU7160

Graefen, B., & Fazal, N. (2024). From chatbots to virtual tutors: An overview of ChatGPT’s role in the future of education. Archives of Pharmacy Practice, 15(2), 43–52. https://doi-org.proxy2.library.illinois.edu/10.51847/TOuppjEDSX

Kalantzis, M., & Cope, B. (2024). Literacy in the time of artificial intelligence. EdArXiv. https://doi.org/10.35542/osf.io/es5kb.

Kalantzis, M., & Cope, B. (2012). New learning : elements of a science of education. Cambridge University Press,. https://doi.org/10.1017/CBO9781139248532

Kropf, D. C. (2013). Connectivism: 21st century’s new learning theory. European Journal of Open, Distance and E-Learning, 16(2), 13–24. https://doi-org.proxy2.library.illinois.edu/https://www.eurodl.org/materials/contrib/2013/Kropf.pdf

Main, P. (2023). Assimilation vs. accommodation [Image]. Structural Learning. https://www.structural-learning.com/post/assimilation-vs-accommodation

Marzuki, Widiati, U., Rusdin, D., Darwin, & Indrawati, I. (2023). The impact of AI writing tools on the content and organization of students’ writing: EFL teachers’ perspective. Cogent Education, 10(2), 1–17. https://doi-org.proxy2.library.illinois.edu/10.1080/2331186X.2023.2236469

Mittal, U., Sai, S., Chamola, V., & Sangwan, D. (2024). A comprehensive review on generative AI for education. IEEE Access, 12, 142733–142759. https://doi-org.proxy2.library.illinois.edu/10.1109/ACCESS.2024.3468368

Ngo Cong-Lem, Tin Nghi Tran, & Tat Thang Nguyen. (2024). Academic integrity in the age of generative AI: Perceptions and responses of Vietnamese EFL teachers. Teaching English with Technology, 24(1), 28–48. https://doi.org/10.56297/FSYB3031/MXNB7567

Raob, I., Al-Oshaibat, H., & Ong, S. L. (2012). A factor analysis of teacher competency in technology. New Horizons in Education, 60(1), 13–22. https://doi-org.proxy2.library.illinois.edu/https://www.hkta1934.org.hk/NewHorizon/index2.html

Reese, S. (2015). Online learning environments in higher education: Connectivism vs. dissociation. Education & Information Technologies, 20(3), 579–588. https://doi-org.proxy2.library.illinois.edu/10.1007/s10639-013-9303-7

Regmi, K. D. (2024). The rise of learning technology in an unequal world: Potentials and limitations in enhancing lifelong learning. International Review of Education, 70(3), 433–452. https://doi-org.proxy2.library.illinois.edu/10.1007/s11159-023-10058-2

Rostami, K., & Khadjooi, K. (2010). The implications of Behaviorism and Humanism theories in medical education. Gastroenterology & Hepatology from Bed to Bench, 3(2), 65–70. https://doi.org/10.22037/ghfbb.v3i2.81

Sangrà, A. and Wheeler, S. (2013). New informal ways of learning: Or are we formalizing the informal? RUSC, 10(1), 286-293. https://10.7238/rusc.v10i1.1689

Shu Wan. (2024).The Jack in the black box: Teaching college students to use ChatGPT critically. Information Technology & Libraries, 43(3), 1–3. https://doi-org.proxy2.library.illinois.edu/10.5860/ital.v43i3.17234

Sidoti, O. (2023, November 16). About 1 in 5 U.S. teens who’ve heard of CHATGPT have used it for schoolwork. Pew Research Center. https://www.pewresearch.org/short-reads/2023/11/16/about-1-in-5-us-teens-whove-heard-of-chatgpt-have-used-it-for-schoolwork/

Siemens, G. (2005). Connectivism: A learning theory for the digital age, International Journal of Instructional Technology and Distance Learning, 2. 

Standridge, M. (2002). Behaviorism. In M. Orey (Ed.), Emerging perspectives on learning teaching, and technology. Retrieved from https://textbookequity.org/Textbooks/Orey_Emergin_Perspectives_Learning.pdf

Turkmen, H. (2006). What technology plays supporting role in learning cycle approach for science education. Turkish Online Journal of Educational Technology - TOJET, 5(2), 71–76.

Uribe S. N., & Vaughan, M. (2017). Facilitating student learning in distance education: a case study on the development and implementation of a multifaceted feedback system. Distance Education, 38(3), 288- 301. http://dx.doi.org/10.1080/01587919.2017.1369005

Utecht, J., & Keller, D. (2019). Becoming relevant again: Applying connectivism learning theory to today’s classrooms. Critical Questions in Education, 10(2), 107–119.