Call for Special Issue on CT in Early Childhood: Guest Blog Post from Wang, Bers, and Lee

In my blog post on what I got wrong in the 2010’s, I pointed to the many definitions of computational thinking (CT) that I had shared in this blog. I said that I hoped that I wouldn’t be offering any more, but I was probably wrong on that too.

Below you will find (yet another) definition of CT, which is pretty intriguing.

---

Early Childhood Research Quarterly
Call for Papers

Special Issue: Examining Computational Thinking in Early Childhood

Guest Editors 

X. Christine Wang, State University of New York at Buffalo, wangxc@gmail.com

Marina Bers, Tufts University, marina.bers@tufts.edu

Victor R. Lee, Stanford University, vrlee@stanford.edu 

Described as the new literacy of the 21^stcentury, computational thinking (CT) is broadly defined as systematic analysis, exploration, and testing of solutions to open-ended and often complex problems based on the analytical process rooted in the discipline of computer science. Driven by the increasing demands for computing professionals, CT has been popularized as a key goal of computer science teaching and learning in K-12 schools. On the one hand, much new research is currently exploring the relationships between CT and coding, CT in everyday unplugged activities, and CT and cognitive and socio-emotional domains of knowledge. On the other hand, there is also heated debate about the validity and applicability of CT, whether CT refers to a new set of competencies, and what value CT has in schooling. Because of the complicated nature of these explorations and conversations, CT has drawn considerable attention in educational research and practice, including early childhood education in recent years (Bers, 2018; Jung & Won, 2018; Toh et al., 2016; Xia & Zhong, 2018). 

To help advance this burgeoning area of research, this special issue seeks empirical and theoretical contributions about young children’s (ages 2-8) CT learning and teaching. We encourage researchers to explore, but not limit themselves to, one or more of the following topics:

(1) Critical examinations of definitions and/or conceptualizations of CT in early childhood

(2) Operationalizations of CT learning goals and practices in early childhood

(3) Developmentally appropriate approaches in promoting CT in early childhood

(4) Relationships between CT and other domains of learning and development

(5) Assessment of CT learning and development in early childhood

(6) Supports for early childhood educators who are bringing CT to young children

(7) Equity and inclusion issues related to CT learning and teaching

For this special issue, we are soliciting a wide range of manuscripts describing rigorous empirical studies, design studies, integrative reviews, theoretical perspectives, or evaluation studies. We welcome studies that employ diverse theoretical and methodological approaches.

Submission Details
We are inviting interested researchers to submit a short proposal prior to manuscript submission. The proposal should be no more than 500 words (excluding references, images, or figures) and must include the following information: (1) Title/Author(s), (2) Key Issues/Problems, (3) Methods/Processes, (4) Findings/Evidence-Based Claims, and (5) Relevance and Contribution to the Special Issue.

Please submit your proposal via email to the Guest Editors with the subject line “ECRQ: CT in Early Childhood”:  X. Christine Wang (wangxc@gmail.com), Marina Bers (marina.bers@tufts.edu), and Victor R. Lee (vrlee@stanford.edu).

The guest editors will provide timely feedback and select proposed papers based on their quality and suitability for this special issue. Selected authors will then be invited to submit a full manuscript.

All full manuscripts must be submitted via the EM system: https://www.editorialmanager.com/ecrq/default.aspx. After you log in and click on “Submit New Manuscript,”  please select “VSI: CT in Early Childhood” on the “Select Article Type” page and proceed accordingly. 

Invitation to submit a full paper will not be a guarantee of acceptance. All manuscripts will undergo the standard ECRQ double-blind peer review procedure. For further information please contact Managing Guest Editor X. Christine Wang (wangxc@gmail.com) or Special Content Editor Gary Resnick (sevenalaris@msn.com).

Deadlines
Proposal submission: July 15, 2021  
Invitation for manuscript submission: August 15, 2021
Manuscript Submission: December 15, 2021
 

Seeking Collaborators for a Study of Impostor Phenomenon in Computer Science: Guest Blog Post from Leo Porter

Impostor Phenomenon (IP)** is often described as high-achieving individuals experiencing feelings of intellectual phoniness.  Based on the research conducted in various fields with different populations over the past four decades, we know that IP causes problems for those who experience it, including being associated with anxiety and depression.  

In computer science, we often hear our colleagues and students talking about their struggles with IP.  There are panels on IP at Grace Hopper and other conferences aimed at helping members of our community cope with these feelings.  But how prevalent is it in CS?

An informal survey conducted by Blind asked participants to self-report their feelings of IP, and among the 10,000 software engineers who participated, 58% reported feelings of IP [5].  However, self-reporting isn’t necessarily an accurate way to measure IP.   In a pilot study at UC San Diego, we used the Clance IP scale [1], a validated instrument that is used in the majority of studies to measure IP.  After administering the Clance IP scale in upper-division and graduate CS courses, we found that 57% of participants met the diagnostic criteria for experiencing IP [7], which was quite similar to that earlier reported finding from Blind.  What was most concerning about our results was the differences for gender among the students:  52% of men met the diagnostic criteria whereas 71% of women did.  That’s a huge (and statistically significant) difference!

But what does this mean?  We can look at results from other studies and see that computer science seems to have higher rates of students who experience IP than in fields like health professionals (31%) [4], undergraduates studying education (28%) [3], undergraduates in business related fields (39%) [8], and undergraduates from racially underrepresented group studying educational psychology (48%) [2].  This suggests that CS may be an outlier with our students struggling more with IP than other fields.  However, a recent study among medical students [6] reported similar results to what we found in CS, suggesting computing might not be alone.

Before we begin asking questions of why CS (and perhaps also medicine) might be outliers, we need to conduct a replication study to verify (or refute) these initial findings from just a single institution.  To that end, we’re putting out a call for other researchers to help participate in a large-scale replication effort to answer these questions:  What is the rate of IP among students in computer science courses?  Does the rate of IP change as students move farther through the curriculum?  Are students from underrepresented groups in computer science more likely to experience IP than those from traditionally represented groups?

If you are willing to be participate in this replication effort, please fill out this brief interest form:

https://forms.gle/MWYPFnmepWT9nMzNA

For those participating, we’ll ask that you administer the instrument in at least one course at your institution.  If you are interested, we’ll also invite you to engage in the data analysis and authoring of any related publications.  We’ll also help you obtain Human Subjects approval at your institution or leverage our approved protocol at UC San Diego.

** Impostor Phenomenon is the original term [1], however Impostor Syndrome and Impostor Phenomenon are commonly used interchangeably.

References

1. Sabine M. Chrisman, W. A. Pieper, Pauline R. Clance, C. L. Holland, and Cheryl Glickauf-Hughes. 1995. Validation of the Clance Impostor Phenomenon Scale. Journal of Personality Assessment 65, 3 (1995), 456–467.
2. Kevin Cokley, Leann Smith, Donte Bernard, Ashley Hurst, Stacey Jackson, Steven Stone, Olufunke Awosogba, Chastity Saucer, Marlon Bailey, Davia Roberts. 2017. Impostor feelings as a moderator and mediator of the relationship between perceived discrimination and mental health among racial/ethnic minority college students. Journal of Counseling Psychology 64, 2 (2017), 141–154.
3. Joseph R. Ferrari. 2005. Impostor Tendencies And Academic Dishonesty: Do They Cheat Their Way To Success? Social Behavior and Personality: an international journal 33, 1 (2005), 11–18.
4. Kris Henning, Sydney Ey, and Darlene Shaw. 1998. Perfectionism, the impostor phenomenon and psychological adjustment in medical, dental, nursing and pharmacy students. Medical Education 32, 5 (1998), 456–464.
5. Kim. 2018. 58 Percent of Tech Workers Feel Like Impostors. https://blog.teamblind.com/index.php/2018/09/05/58-percent-of-tech-workers-feel-like-impostors
6. Beth Levant, Jennifer A. Villwock, and Ann M. Manzardo. 2019. Impostorism in third-year medical students: an item analysis using the Clance impostor phenomenon scale. Perspectives on medical education (2020), 1-9.
7. Adam Rosenstein, Aishma Raghu, and Leo Porter. 2020. “Identifying the prevalence of the impostor phenomenon among computer science students.” Proceedings of the 51st ACM Technical Symposium on Computer Science Education.
8. Kenneth T. Wang, Marina S. Sheveleva, and Tatiana M. Permyakova. 2019. Imposter syndrome among Russian students: The link between perfectionism and psychological distress. Personality and Individual Differences 143 (2019), 1–6.