Computational Creativity Research Articles

Nonknowledge in Computation. Reflecting on Irrevocable Uncertainty

Abstract My paper approaches the theme of computational creativity by looking at uncertainty as an epistemic and aesthetic tool that must be examined to address the challenges brought to critical practice by planetary computation. It positions uncertainty as central to how the encounter of the human practitioner with non-human machines is conceptualized, and as a resource for building speculative-pragmatic paths of resistance against algorithmic capture. It proposes ways to cultivate uncertainty and use it as a design material to produce new types of knowledge that question machines’ pre-emptying manoeuvres and resist their capture of potential. The argument proposed is that uncertainty affords the production of new imaginaries of the human-machine encounter that can resist the foreclosure of futures (what will be) and are sustained instead by the uncertainty of potential (what might be) (Munster 2013). Dwelling in a space of potential – Deleuze’s virtual, or what I call a space of ‘maybes’, requires of the practitioner a repositioning of their epistemic perspective and reflecting on the following questions: how can material knowledge be made by engaging with modes of un-knowing and not-knowing in machine interaction? How can these modes of un-knowing and not-knowing be fostered as a critical and political onto-epistemological project of reinventing critical practice for the algorithmic age? (Horl et al. 2021; Hansen 2021, 2015, Pasquinelli and Joler 2020). The paper argues that the machinic unknown should be engaged with - not through the conventional paradigm that pitches human vs machine creativity and attempts to rank and score them through similarities, but rather through a (paradoxical) deepening of the unknowability at the core of the machine (Parisi) and machine’s own incommensurability (Fazi 2020). It then proposes the Chinese notion of wu wei (active non action) (Jullien 2011, 2004, 2000, 1995; Allen 2015, 2011) as a stratagem to experiment with to craft speculative-pragmatic interventions, and to augment the ‘power of maybes’ as a space of anti-production, and resisting reduction (Ito 2019).

<span><strong>Researching</strong><strong> STEAM in early childhood education between 2013-2023: A bibliometric analysis of Scopus database</strong></span>

This study investigates global research trends on STEAM in early childhood education from 2013 to 2023. The bibliometric analysis method was utilized to analyze a dataset of 129 documents extracted from the Scopus database. The results reveal a growing interest in this field, with a notable increase in the number of publications from 2019 to 2023 compared to 2013-2018. The USA leads in both the number of publications and citations. "Early Childhood Education Journal" is the most prominent, while “Sullivan A” and “Bers MU” gain the most significant impact on this research topic. This review study identifies four main thematic clusters: (1) core aspects of STEAM in early childhood education, (2) gender equality in STEAM education, (3) technology and engineering education, and (4) applying this approach to early childhood education. Research trends indicate a growing interest in topics such as computer literacy, creativity, and children's learning processes in STEAM education. The authors propose several recommendations to guide future research in this area.

Unplugged activities in the elementary school mathematics classroom: The effects on students’ computational thinking and mathematical creativity

The rapid development of artificial intelligence technology has led to the proliferation of computational thinking (CT) education. However, research on unplugged activities’ influence in elementary math classrooms is limited, despite some exploring programming's cognitive benefits. This study presents both qualitative and quantitative analyzes stemming from a ten-week quasi-experimental research endeavor, specifically tailored for third-grade students. The research devised a series of unplugged activities, encompassing mathematical games, hands-on construction of mathematical logic boards, and calculating shopping discounts. The overarching objective was to investigate the impact of these unplugged activities on students’ mathematical creativity and CT. Students participating in a mathematics curriculum based on unplugged activities (N = 47) were compared with students participating in a traditional lecture-based mathematics curriculum (N = 46). The results indicated that unplugged activities exhibited significant advantages in fostering students’ CT and mathematical creativity across three dimensions, namely, problem-posing creativity (t = 5.830, p < 0.01), problem-solving creativity (t = 6.633, p < 0.01), and creative self-efficacy (t = 7.554, p < 0.01). Furthermore, the study revealed a relationship between students’ mathematical creativity as a predictor of CT. The results of the quantitative analysis were supported by the teacher's and students’ interview data, and the students felt excited and interested in the unplugged activities, whereas some students using the lecture-based method reported boredom and lack of interactivity. This research offered valuable insights for mathematics and CT education practice, underscoring unplugged activity as an innovative instructional approach that brings forth new possibilities for traditional mathematics teaching, with potential applications in the K-12 curriculum.

Effects of a Creativity-Enhancement Intervention on Preservice Elementary Teachers’ Creativity in Computing Education

AbstractRecently, creativity has been acknowledged for its importance in improving computer science learning and attitudes. However, very little is known about how to integrate creativity in preservice teacher computing education. Toward this end, we developed a creativity-enhancement intervention in an online Creative Computing instructional module to introduce preservice elementary teachers (N = 76) to the ideas of creativity in the context of computing education. Using a pre-/posttest quasi-experimental design, we examined the effects of the creativity-enhancement intervention on participants’ person-, process-, and Scratch product-related creativity compared to the same curriculum that did not include the creativity-enhancement intervention. Preservice elementary teachers who received the creativity-enhancement intervention reported significantly higher person- and process-related creativity and produced more creative Scratch projects than their peers who did not receive the intervention. When looking at the three creativity strands holistically, the study findings provide strong evidence that the intervention had a positive effect on preservice elementary teachers’ creativity in the context of computing education.

A framework for extending co-creative communication models to sustainability research.

The UN Sustainable Development Goals (SDGs) present a challenge due to their potential for conflicting objectives, which hinders their effective implementation. In order to address the complexity of sustainability issues, a framework capable of capturing the specificity of diverse sustainability issues while offering a common methodology applicable across contexts is required. Co-creative communication can be regarded as a key source of uncertainty within functional systems, as it can be instrumental in realizing and sustaining sustainability. In this regard, the studies in Constructive approaches to Co-creative Communication (CCC), particularly those employing artificial intelligence (AI) methodologies such as computational social science and innovation studies, hold significant value for both theoretical and applied sustainability research. However, existing CCC frameworks cannot be directly applied to sustainability research. This work bridges this gap by proposing a framework that outlines a general approach to establishing formalized definitions of sustainability from the lens of communication. This approach enables the direct application of CCC models to sustainability studies. The framework is based on systems theory and the methodologies of artificial intelligence, including computational/symbolic modeling and formal methods. This framework emphasizes the social function of co-creative communication and the interaction between the innovation process and the sustainability of the system. It can be concluded that the application of our framework enables the achievements of CCC to be directly applied to sustainability research. Researchers from different disciplines are therefore able to establish their own specific definitions of sustainability, which are tailored to their particular concerns. Our framework lays the groundwork for future sustainability studies that employs CCC, facilitating the integration of CCC insights into sustainability research and application. The outcomes of computational creativity research based on AI technologies, such as distributed artificial intelligence and self-organizing networks, can deepen the understanding of sustainability mechanisms and drive their practical applications. Furthermore, the functional role of co-creative communication in societal sustainability proposed in this work offers a novel perspective for future discussions on the evolutionary adaptation of co-creative communication.

Effects of Teachers’ Media Utilization and Computational Thinking on Sustainable Development in Early Childhood Education

(1) Background: The study aims to analyze the degree of media use among early childhood teachers and the correlations between their computational thinking, playfulness, creativity, and problem-solving abilities. It confirms a strong correlation between playfulness and problem-solving abilities and investigates whether higher levels of computational thinking are associated with higher levels of playfulness. This research is positioned within the context of sustainable development in early childhood education, emphasizing the importance of integrating digital literacy and computational thinking skills to promote sustainability. (2) Methods: The research was conducted on teachers working in daycare centers and kindergartens in Jeju Island, South Korea. A total of 203 questionnaires were collected, employing descriptive statistics, frequency analysis, Pearson’s correlation coefficient analysis, one-way ANOVA, and multiple regression analysis. (3) Results: The study found that teachers’ degree of media literacy affects their media use. Additionally, the higher the degree of computational thinking, the more significant the effect on early childhood teachers’ playfulness. Furthermore, early childhood teachers’ playfulness, creativity, and problem-solving skills were all significantly correlated overall. (4) Conclusions: The findings suggest that if teachers take an interest in IT media and find ways to use it positively, it will have a positive effect on early childhood education. Moreover, increasing computational thinking skills will enable the effective use of various tools, positively impacting teachers’ roles. The study proposes that enhancing early childhood teachers’ playfulness, creativity, and problem-solving skills will contribute to sustainable development in early childhood education.

Creativity and Machine Learning: A Survey

There is a growing interest in the area of machine learning and creativity. This survey presents an overview of the history and the state of the art of computational creativity theories, key machine learning techniques (including generative deep learning), and corresponding automatic evaluation methods. After presenting a critical discussion of the key contributions in this area, we outline the current research challenges and emerging opportunities in this field.

Amplifying the Anomaly: How Humans Choose Unproven Options and Large Language Models Avoid Them

ABSTRACT Both large language models (LLMs) and the human brain develop internal models of reality to make accurate predictions. Both typically prefer choices with the strongest track records. However, when faced with a creative challenge, LLMs remain committed to high-probability options while humans can opt for unproven ones. This paper delves into one way of making unlikely events plausible—“amplifying the anomaly.” The concept involves extrapolating viable consequences from an unlikely proposition. Rather than being treated as oddball events or “one-offs,” the anomaly permeates the creative work. Notably, novelty and appropriateness can be in tension with each other, with high utility coming at the cost of low novelty. Amplifying the anomaly aligns these competing demands. It enhances originality: the rarer a proposition and the more thoroughly it is worked out, the more unique and surprising the result. At the same time, the effectiveness and value of the unproven option also rises: thorough elaboration in the creative product establishes its fitness. Musical examples by Beethoven, Schubert, and contemporary composer Skye Macklay, along with creative products from other domains, illustrate this principle. Classic LLMs have several limitations that make it difficult to amplify the anomaly: they are steered toward norm-driven outcomes, make short-term decisions, and are not designed to self-evaluate. As a result, they have difficulty of developing unusual propositions in a non-obvious way without human guidance. Alternatives approaches, including adversarial networks and team AI, are briefly examined. Implications for the future of computational and human creativity are discussed.

Improving 6th Grade Students’ Creative Problem Solving Skills Through Plugged and Unplugged Computational Thinking Approaches

In the digital age in which we live, one of the primary goals of education is to nurture individuals who are capable of thinking creatively, solving problems, and being innovative and productive. Computational thinking is an analytical process that requires defining problems and at the same time solving these problems by proceeding in creative ways. Based on this possible pattern of relationship between computational thinking and creativity, the aim of this study was to determine how two different versions of the computational thinking approach (plugged and unplugged) affect 6th-grade students' creative problem-solving skills (CPSS). Thus, two different teaching modules were designed on the circulatory system with a focus on plugged and unplugged computational thinking. A quasi-experimental design was used. Experiment group 1 utilized the plugged teaching module, experiment group 2 worked with the unplugged teaching module, and the control group in the Turkish middle school science curriculum's inquiry-based science activities. All three groups participated in 16 h of lessons over a 4-week period. We utilized the Creative Problem Solving Skills Inventory (CPSSI) for data collection. The results demonstrated that both the plugged and unplugged teaching modules were more successful at enhancing the CPSS than the inquiry-based science activities. Furthermore the unplugged teaching module was significantly more successful in developing CPSS compared to inquiry-based science activities. Hence, this empirical study demonstrated that both plugged and unplugged computational thinking approaches can enhance CPSS, but also reveals the greater effectiveness of unplugged approaches in fostering middle school students' CPSS.

Computational creativity of neural network Midjourney in a polymodal space

This article deals with the polymodal space in the field of computational creativity in neural networks. The object of research is a polymodal environment that integrates a series of heterogeneous codes to express a common idea, and the subject is the possibility of creating polymodal digital art using text and voice prompts in the generative network Midjourney. The aim of the study is to prove that computational creativity can be detected and described based on the results of iterations in the process of creating images, which in turn will allow us to talk about a complex polymodal system as a separate digital category of polymodality. We used the continuous sampling method when collecting linguistic units as they occur in the analysis process; contextual analysis for the systematic identification and description of the verbal and non-verbal contexts. It was necessary to conduct an experiment with the generative network Midjourney to identify patterns in the creation of a graphic space through text and voice data input, and then compare and contrast the results of iterations with the original image. The scientific novelty consists in the lack of research on the polymodal space in the context of neural networks and their generative ability. During the experiment, we obtained the following results: the term ‘polymodality’ in the context of the generative network Midjourney and its ‘digital art’ is due to the presence of three channels: verbal, visual and voice; tests have shown that the ability of the neural network to create images through prompt is at a high level, however, there are rough technical errors that do not allow users to fully approach the desired result when they generate an image; the summarization of the data allows us to talk about the presence of features of computational creativity in generative networks.

The effectiveness of using educational robots in enhancing engineering mathematics skills among students in basic school

Educational robots foster engaging, democratic, and collaborative learning environments, enhancing students' mathematical and engineering abilities by enabling them to interact, solve problems, assimilate information, and communicate effectively within the classroom. This study aims to examine the impact of educational robots on the development of engineering mathematics skills. The study uses a quantitative approach with a quasi-experimental design for a single pre- and post-test group. The sample consisted of 40 fifth grade students who initially studied geometry using traditional methods, followed by studying the same content using the educational robot. The study found that robot-based education significantly improved engineering mathematics skills. It was concluded that using educational robotics as a tool for teaching mathematics improved computational thinking, engineering mathematics, motivation, creativity, cooperation, and teamwork. It is possible to argue that the study's results corroborate relevant research showing how educational robots raise students' academic performance and improve their critical thinking. These results lend credence to the idea that educational robots improve learning beyond traditional approaches by actively involving students, giving subjects greater concreteness, and capturing their interest and attention. The study recommends the creation of new mathematical activities using educational robots across various mathematical contents and educational stages, further enhancing engineering mathematics among students.

AI art and public literacy: the miseducation of Ai-Da the robot

This article examines the implications of the artworks and public performances of the robot artist Ai-Da. While the project claims to advance AI public literacy and foster critical debate around intelligent systems, it instead ends up perpetuating popular misunderstandings about AI creativity, agency, and consciousness. Built in 2019, Ai-Da is a humanoid robot capable of creating drawings, paintings, and composing poetry. However, the project often conceals or miscommunicates the technical aspects of Ai-Da’s capabilities in a manner that encourages the public to misattribute human-like traits to the robot. This lack of transparency in the presentation of Ai-Da’s abilities and the creative processes involved risks reinforcing existing misconceptions about AI, rather than promoting a more nuanced understanding. By employing discourse analysis and drawing on scholarship on machine and computational creativity, anthropomorphism in social robots, and posthuman embodiment, this article uses the Ai-Da project as a case study to illustrate how the dangers of AI hype can be obscured when presented through the lens of public art. The analysis examines how the Ai-Da project, despite its stated goals of advancing AI literacy, fails to effectively challenge and may even exacerbate public misperceptions about the nature of AI-generated art and creativity.

Melody Generation using Deep Learning: Unleashing the Power of RNN and LSTM

This project aims to develop a novel approach for piano melody generation using Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) models in deep learning.The suggested models will be trained on a dataset of MIDI files with piano melodies to use sequential learning capabilities and capture the complex patterns and relationships present in musical compositions. [1] The project aims to gen- erate a variety of melodies that are both musically coherent and diverse by experimenting with various network designs, hyperparameters, and training procedures. The developed tunes will be evaluated primarily on their originality, conformity to stylistic elements, and general quality. The results of this study could lead to new developments in AI-driven music composition as well as opportunities for computational creativity in the music industry.

When Language is Played: Looking into Linguistic Creativity through Language Play

Abstract This article opens a window on linguistic creativity through an in-depth discussion of language play. To this aim, language play is initially conceptualized from a socio-cognitive perspective. ‘Language play for fun’ and ‘language play for practice’ as two dominant approaches in the relevant literature are, then, touched upon. Afterward, the paper elucidates how language play, in its various manifestations, can inform and influence linguistic creativity. In this respect, a theoretical (linguistic) and a socio-pragmatic perspective are presented. In particular, the paper addresses the possibility of playing to ‘language’ outside the box (i.e., to go beyond the conventional systemic constraints of language). Highlighting the ubiquity of language play, it also considers Wittgenstein’s notion of ‘language games’ (or Sprachspiele). Furthermore, the performative power of playful creativity to make and ‘unmake’ language in society is elaborated on. The article contends that language play may offer valuable insights to extend the borders of linguistic creativity. This argument is further developed under the purview of ‘complexity theory,’ ‘soft computing,’ and ‘computational linguistic creativity.’ Finally, the paper advocates an ‘integrated science’ approach to advance play-based research on linguistic creativity.

Operationalizing Essential Characteristics of Creativity in a Computational System for Music Composition

We address the problem of building and evaluating a computational system whose primary objective is creativity. We illustrate seven characteristics for computational creativity in the context of a system that autonomously composes Western lyrical music. We conduct an external evaluation of the system in which respondents rated the system with regard to each characteristic as well as with regard to overall creativity. Average scores for overall creativity exceeded the ratings for any single characteristic, suggesting that creativity may be an emergent property and that unique research opportunities exist for building CC systems whose design attempts to comprehend all known characteristics of creativity.

Development of an exploratory creativity assessment scale

ABSTRACT Exploratory creativity (E-creativity) can be achieved by searching an area of conceptual space governed by specific rules. Existing studies on E-creativity mainly focus on how to use aspects of E-creativity to develop computational creativity tools, but E-creativity assessment scales have not been fully studied. To fill in the gap, this study developed an E-creativity assessment scale based on metrics and experimental determination studies. Eight indexes are promoted through literature investigation, which are related to E-creativity attributes, pre-requirement for the existence of E-creativity, relations between exploratory process and creativity, and results of E-creativity. Then, an empirical case study is applied to investigate the differences between nonprofessionals and professionals when using the developed scale. From the whole research, the results reveal that E-creativity is not simply related to the exploratory process and its concept space; instead, it is also related to the relations between the novelty of the exploratory process and the concept space of E-creativity. The results reflect the role of E-creativity in a creative process. This research provides a further understanding of E-creativity, which can contribute to further develop the definition of E-creativity. The E-creativity assessment scales can be used as a cue to further evaluate machine generated E-creativity.

Creative learning in final year students in computer engineering: A case study of the University of Matanzas

The training of creative computer professionals is considered a strategic process in different countries because it is essential for the computerization of society. This paper proposes an approach to the study of creative computer science learning for the digital transformation of modern society. The aim of the research was to evaluate the creative learning of computer science during the training of computer science professionals. An instrument derived from previous research and metrics was applied to evaluate creative learning in the two groups of terminal years of the computer engineering course at the University of Matanzas with a mixed paradigm. The quantitative analysis diagnosed that more than sixty-five percent of the students are evaluated as poor and fair in both years. The qualitative analysis revealed the inadequacies of the teaching staff in the use of computer science teaching approaches, and the four stages of formation of creative learning in computer science in the degree course: pre-university stage, basic stage, professional stage and research stage. They also revealed three key factors in the formation of creative learning in computer science: the integration of subjects, the solution of real projects, and the mainly emotional support provided by teachers and other professionals to students during their integration into the computerization of organizations.

Classical Turkish Music Composition with LSTM Self-Attention

Synthetic symbolic music generation, the process of creating new musical pieces using symbolic representations, has gained significant traction in the field of music informatics and computational creativity. It holds immense potential for various applications, ranging from music education and composition assistance to music therapy and personalized music recommendation systems. Classical Turkish music (CTM) exhibit distinct characteristics regarding Western Tonal Classical Music (WCM) such as melodic organization, formation of rhythmic structure or melodic expressions. This study tackles the challenge of symbolic music composition, focusing on CTM. Unlike WCM, CTM incorporates microtonal intervals. These intervals are smaller than the semitones in Western music, allowing for a more nuanced expression of pitch. This leads to a more diverse set of pitch ranges. The proposed method employs a combination of self-attention and long-short term memory (LSTM) networks to capture long-term relational information and generate realistic CTM compositions. LSTMs effectively model sequential dependencies and improve local relations within musical structures and self-attention improves the context vector, allowing the model to attend to different aspects of the musical context simultaneously. This combination enables the proposed method to generate compositions that are both musically coherent and stylistically consistent with distinct features of CTM. The proposed method was evaluated on two datasets, the CTM dataset and Classical Music Piano (CPM) dataset. The assessment of musical contents is evaluated through melodic similarity and stylistic consistency metrics. The results demonstrate that the proposed method is able to generate musical content that is coherent and produce music that is pleasing-to-hear. Overall, the article presents a novel and effective approach to symbolic music composition, focusing on CTM.

TRENDS IN STUDIES ON EDUCATIONAL ROBOTICS IN RECENT YEARS: A CONTENT ANALYSIS

This study aims to analyze the general trends in educational robotics in recent years. The document analysis method was preferred in this research. Accordingly, the content of 100 articles published in the field of educational robotics in recent years was analyzed in terms of methodology, sample characteristics, robotic tools used, commonly covered topics, and findings. The study revealed that Lego Mindstorms, Arduino, Python, and Scratch are the most commonly used robotic tools in educational robotics. It was observed that students predominantly participated in the studies, with a focus on university and middle school levels. Moreover, the analysis indicated that quantitative studies mostly employed scales and questionnaires, whereas qualitative studies frequently used interviews and observation forms as measurement tools. The most frequently examined variables in these studies were computational thinking, problem-solving, creativity, academic achievement, collaboration, and motivation. While the findings generally emphasized the positive effects of educational robotics and its significance for integration into other domains, the challenges of educators’ knowledge and experience in robotics, infrastructure and technical issues, and difficulties in practical implementation were also identified as disadvantages.

Enhancing Project-Based Learning in STEM Education with Integrated Technology and Coding

This extensive study explores the advantages and significance of incorporating technology and coding into project-based learning to improve STEM education. This integration improves students' learning experiences by encouraging computational thinking, problem-solving ability, and creativity. Collaborative coding projects promote interdisciplinary learning and a thorough comprehension of multiple subjects, while online resources and self-paced learning platforms enable students to study coding outside of the classroom. Educators can design meaningful learning experiences that match technology use with learning objectives and stimulate social connections and cooperation by embracing theories such as constructivism, TPACK, and social constructivism. Inquiry-based learning, project-based learning, and self-regulated learning are all strategies that promote student engagement and learning in integrated technology and coding. Providing resources, professional development opportunities, and technical support systems promotes in efficient implementation. Educators may develop engaging project-based learning experiences that equip students with necessary skills for the future by embracing creative techniques and incorporating technology and coding.