Academic Communication Inventory (ACI)

Abstract

The Academic Communication Inventory (ACI) is a psychometric instrument developed to assess academic communication among undergraduate university students. Conceptualized as an operationalization of how learners strategically mobilize social and interpersonal communication behaviors to foster educational achievement, the ACI addresses a critical gap in higher education assessment by differentiating communication modalities across distinct interpersonal targets. Developed through rigorous exploratory and confirmatory protocols initiated from an original pool of 29 items derived from qualitative focus groups and empirical literature, the instrument was systematically refined into a concise 12-item self-report scale. The inventory is structured around two distinct, correlated dimensions: Communication With Instructors (7 items) and Communication With Peers (5 items). Items are rated on a 5-point Likert-type scale. Psychometric evaluations across multiple undergraduate cohorts demonstrate robust internal consistency, yielding Cronbach’s alpha coefficients of .88 for the instructor-focused dimension and .86 for the peer-focused dimension. Confirmatory factor analyses support a two-factor correlated structure exhibiting solid fit indices (χ² = .001, CFI = .90, RMSEA = .080, SRMR = .073). Item Response Theory (IRT) analyses substantiate the unidimensionality of the individual subscales, while multigroup structural equation modeling establishes configural, metric, and scalar measurement invariance across differing course environments. Convergent validity is confirmed through moderate, statistically significant correlations with validated measures of student engagement (r = .424 to .437). The ACI provides researchers, educational psychologists, and academic developers with an empirically sound, versatile diagnostic tool capable of evaluating both generalized and course-specific communicative patterns in postsecondary educational settings.

Keywords

Academic Communication, Academic Communication Inventory, Higher Education, Communication with Instructors, Communication with Peers, Student Engagement, Psychometrics, Factor Analysis, Measurement Invariance, Undergraduate Students

Authors

The Academic Communication Inventory was developed and validated by researchers specializing in developmental psychology, educational environments, and instructional development:

• Kristen A. Archbell, Ph.D.
  Affiliation: Centre for Teaching Excellence, University of Waterloo, Waterloo, Ontario, Canada.
  Email: [email protected]
  Correspondence Address: Centre for Teaching Excellence, University of Waterloo, 200 University Avenue West, Waterloo, Ontario, Canada, N2L 3G1.
• Robert J. Coplan, Ph.D.
  Affiliation: Department of Psychology, Carleton University, Ottawa, Ontario, Canada.
  ORCID Identifier: 0000-0000-3696-2108.

Purpose

The transition into postsecondary education demands that students navigate complex, self-directed learning environments where academic success is heavily contingent upon proactive social interaction. The primary purpose of the Academic Communication Inventory (ACI) is to provide an empirical, standardized measure of academic communication—defined as the goal-directed communicative acts that undergraduate students deploy to advance their coursework, clarify disciplinary concepts, resolve logistical ambiguities, and integrate into collegiate academic communities. Prior to the development of the ACI, higher education researchers frequently relied on fragmented proxies for student participation, such as general classroom participation frequencies, broad social self-efficacy metrics, or unstructured behavioral check-sheets. These historic approaches failed to isolate the targeted, academic intent behind interpersonal interactions or delineate the structural differences between interacting with institutional authority figures versus peers.

From an applied perspective, the ACI serves dual diagnostic functions in institutional research and intervention planning. In research contexts, the scale enables investigators to examine the complex predictive mechanisms linking communicative behaviors to academic self-efficacy, psychological well-being, social anxiety, loneliness, retention, and cumulative grade point averages (GPA). Because the ACI was formulated to possess contextual versatility, it can be administered either as a macro-level assessment evaluating an undergraduate student’s generalized communication tendencies across an entire academic term or as a micro-level, course-specific assessment investigating communicative barriers within a targeted discipline (e.g., large introductory STEM lectures versus small humanities seminars).

In educational development and academic counseling, the ACI operates as a diagnostic instrument for identifying undergraduates at risk of academic marginalization. For example, students exhibiting elevated academic anxiety or imposter phenomena may demonstrate normal peer communication while completely avoiding interactions with faculty, teaching assistants (TAs), and course instructors. Identifying such asymmetrical communicative profiles allows academic advisors, teaching centers, and student support services to implement evidence-based interventions, such as structured peer-assisted study schemes or office-hour demystification workshops. The theoretical rationale of the ACI asserts that academic communication is not merely an innate personality trait, such as extraversion, but a dynamic, modifiable behavioral repertoire that directly influences how educational resources are negotiated and acquired within higher education ecosystems.

Psychological Construct

The psychological construct assessed by the ACI—academic communication—is conceptualized as an agentic, communicative competency situated at the intersection of educational psychology, social development, and communication studies. Academic communication is distinguished from social communication in that its explicit objective is scholastic progression, intellectual mastery, and the collaborative resolution of educational challenges. The construct recognizes that communicative interactions within modern universities occur across multiple interpersonal hierarchies and via diversified technological mediums, encompassing oral, written, asynchronous, and synchronous channels.

The ACI models academic communication through two primary, interconnected dimensions:

1. Communication With Instructors

This dimension captures communicative interactions directed vertically toward institutional figures of academic authority, including course professors, lecturers, seminar leaders, and graduate teaching assistants (TAs). These interactions carry intrinsic social evaluative weight, as instructors hold institutional power regarding grading, academic standing, and professional endorsement. Communicating with instructors requires students to overcome perceived power differentials, potential fears of negative evaluation, and communication apprehension. Within the ACI, this subscale captures an array of behavioral modalities, including:

• In-class verbal responsiveness (e.g., answering questions posed by instructors during formal lectures).
• Proactive public inquiry (e.g., asking clarifying questions during lectures or seminars).
• Out-of-class individual interactions (e.g., attending physical or virtual office hours held by instructors or TAs).
• Logistical self-advocacy (e.g., scheduling formal appointments to review coursework or clarify expectations).
• Institutional digital engagement (e.g., contributing substantive queries on instructor-monitored learning management system [LMS] discussion boards).

2. Communication With Peers

This dimension encompasses horizontal, collaborative communicative behaviors initiated among fellow undergraduate learners. Horizontal academic communication represents collaborative socio-cognitive scaffolding, wherein peers exchange cognitive perspectives, share study resources, co-construct knowledge, and provide reciprocal emotional and academic support. In modern digital learning spaces, academic peer communication extends far beyond casual face-to-face dialogue to incorporate technologically mediated modalities. The ACI evaluates this dimension across behaviors such as:

• Informal, out-of-class course discussions (e.g., reviewing syllabus concepts and challenging lecture themes face-to-face).
• Direct mobile communication (e.g., sending text or SMS messages regarding assignment parameters and exam dates).
• Social network-mediated messaging (e.g., utilizing instant messaging applications on social platforms to troubleshoot homework problems).
• Collaborative virtual group participation (e.g., joining or creating dedicated study groups on platforms such as Discord, WhatsApp, or Slack).
• Co-constructive document sharing (e.g., creating and editing collaborative cloud-based documents on Google Drive or Notion to organize collective study guides).

Theoretical Framework

The design and operationalization of the Academic Communication Inventory are grounded in established socio-cognitive, constructivist, and developmental frameworks that emphasize the social nature of learning. Three primary theoretical perspectives underpin the ACI:

Socio-Cultural Theory and the Zone of Proximal Development

Rooted in the seminal framework of Lev Vygotsky, socio-cultural learning theory posits that higher cognitive functions originate through social interaction and dialogue. Learning is essentially mediated through cultural tools, language, and semiotic signs. Within postsecondary environments, knowledge is co-constructed through discursive practices with more knowledgeable others (instructors and teaching assistants) as well as equal-status partners (peers). When students engage in academic communication, they actively traverse their Zone of Proximal Development (ZPD). Instructors provide cognitive scaffolding by answering questions and clarifying conceptual boundaries, while peer dialogue provides peer scaffolding, encouraging cognitive elaboration, mental restructuring, and the reconciliation of conflicting conceptual models.

Social Cognitive Theory and Academic Self-Efficacy

Albert Bandura‘s Social Cognitive Theory emphasizes the dynamic triadic reciprocal determinism between personal cognitive factors, environmental influences, and overt behavioral patterns. Academic communication represents an agentic behavioral strategy through which students actively shape their educational environment. A student’s decision to ask a question during a lecture or message a peer about an upcoming assignment is influenced by their academic self-efficacy and outcome expectations. In turn, successful communicative episodes serve as mastery experiences and sources of verbal persuasion, reinforcing academic agency and self-regulated learning skills.

Student Integration and Engagement Models

The ACI aligns with sociological and educational persistence paradigms, notably Vincent Tinto‘s Model of Student Departure and modern theories of student engagement (e.g., George Kuh). Tinto posited that college persistence is fundamentally determined by a student’s degree of academic and social integration into the institution. Formal and informal contact with faculty members has consistently emerged as one of the strongest empirical predictors of undergraduate retention, institutional commitment, and intellectual growth. By separately capturing interactions with instructors (academic/institutional integration) and peers (social/collaborative integration), the ACI provides an operational bridge linking micro-level behavioral communications to macro-level retention and engagement theories.

Validity

The psychometric validity of the Academic Communication Inventory was established through a series of empirical investigations detailing content, structural, convergent, and contextual validity across independent samples of undergraduate students.

Content and Face Validity

The content validation process began with an exhaustive review of higher education and instructional communication literature, paired with structured qualitative focus groups conducted with undergraduate students. This inductive-deductive approach ensured that the preliminary 29 items comprehensively reflected contemporary communication avenues, explicitly addressing both traditional face-to-face interactions (e.g., attending physical office hours) and technologically mediated exchanges (e.g., social networks, collaborative digital documents, LMS discussion boards). Subject matter experts in educational psychology evaluated the items for clarity, construct fidelity, and developmental appropriateness for young adults in university environments.

Convergent Validity

Convergent validity was evaluated by examining bivariate correlations between the ACI subscales and validated measures of student engagement (SE). Theoretical models hypothesize that students who frequently initiate academic communication will exhibit greater behavioral, cognitive, and affective engagement with their academic programs. In empirical validation studies, both ACI factors demonstrated moderate, statistically significant positive correlations with overall student engagement:

• Communication With Peers: Demonstrated a positive correlation of r = .437 (p < .001) with student engagement.
• Communication With Instructors: Exhibited a positive correlation of r = .424 (p < .001) with student engagement.

These moderate effect sizes substantiate that while academic communication is fundamentally intertwined with broader student engagement, it remains a distinct behavioral construct rather than a redundant proxy for general involvement.

Measurement Invariance and Contextual Validity

To evaluate whether the ACI operates reliably across varied educational settings, the authors conducted multigroup confirmatory factor analyses examining measurement invariance across course contexts (e.g., general multi-course academic life versus specific course environments). The ACI successfully achieved:

• Configural Invariance: Demonstrating that the two-factor conceptual structure is identical across differing educational contexts.
• Metric (Weak) Invariance: Indicating that the factor loadings are equivalent across contexts, confirming that students interpret the behavioral indicators with the same conceptual metric.
• Scalar (Strong) Invariance: Establishing that item intercepts are invariant across groups, which permits meaningful comparisons of latent and observed factor means across different instructional modalities and classroom environments.

Reliability

The reliability of the Academic Communication Inventory has been systematically confirmed across independent undergraduate samples, demonstrating robust internal consistency across its constituent subscales.

Internal Consistency

Classical test theory reliability coefficients indicated high internal consistency for both subscales following structural optimization:

• Communication With Instructors Subscale: Yielded a Cronbach’s alpha of α = .88 across the initial 10-item validation pool, retaining high consistency (α ≥ .86) in the finalized 7-item structure. Significant inter-item correlations within this factor ranged from r = .32 to .89, demonstrating that while items share a common core construct, they assess distinct aspects of instructor-targeted communication.
• Communication With Peers Subscale: Yielded a Cronbach’s alpha of α = .86 across the initial 8-item pool and demonstrated comparable reliability across the finalized 5-item metric. Inter-item correlations within the peer dimension ranged from r = .28 to .79, reflecting a coherent but non-redundant behavioral spectrum ranging from direct messaging to collaborative digital authoring.

Item Response Theory (IRT) Evidence

Beyond traditional classical test theory, the psychometric properties of the ACI items were scrutinized using Item Response Theory (IRT). The IRT analyses confirmed the unidimensionality of each underlying subscale, verifying that individual items within the subscales measure their intended latent trait. Although local item dependencies were observed among items sharing identical communicative platforms (such as mobile text messaging and social network messaging), the discrimination parameters remained elevated, confirming that the scale items effectively differentiate between students with varying levels of academic communicative initiative.

Factor Analysis

The structural architecture of the ACI was determined through a multi-step analytical progression combining exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modeling across two independent university cohorts.

Exploratory and Principal Axis Factor Analysis

Initial factor structure investigations utilized Principal Axis Factoring on the preliminary 29-item questionnaire. The unrestricted extraction initially pointed to an over-factored six-factor solution characterized by several weak factors, cross-loadings, and platform-specific groupings. Following psychometric guidelines, problematic items displaying low primary factor loadings (< .40) or high cross-loadings (> .30 on secondary factors) were sequentially pruned. Analysis of the remaining 18 items suggested a 4-factor solution, which was subsequently re-evaluated with fixed three-factor and two-factor extractions. The fixed two-factor model proved the most parsimonious and theoretically coherent, accounting for 50% of the total cumulative variance.

Confirmatory Factor Analysis (CFA)

To validate the hypothesized dimensional structure, Confirmatory Factor Analysis was conducted on an independent sample. The empirical data corroborated that a two-factor correlated model—separating Communication With Instructors from Communication With Peers—provided the optimal structural fit for the data. The final fit statistics for the model met conventional psychometric criteria:

• Chi-Square (χ²): p = .001
• Comparative Fit Index (CFI): .90
• Root Mean Square Error of Approximation (RMSEA): .080 (90% CI [.071, .089])
• Standardized Root Mean Square Residual (SRMR): .073
• Akaike Information Criterion (AIC): 14646.20
• Bayesian Information Criterion (BIC): 14870.06

The structural model established that the two latent factors correlate positively (typically r ≈ .35 to .45), demonstrating that while both factors reflect an underlying willingness to communicate academically, they represent distinct behavioral trajectories that can vary independently within individual students.

Instrument / Measurement Tool

The Academic Communication Inventory is structured as follows:

• Test Type: Self-report questionnaire / psychometric behavioral inventory.
• Target Population: Undergraduate university students (typically ages 17 to 25 years; applicable to young adults and adult learners).
• Administration Modality: Paper-and-pencil or computerized digital survey (LMS, Qualtrics, REDCap).
• Duration: Approximately 3 to 5 minutes to complete.
• Item Count: 12 standardized items in the finalized scale (7 items for Instructors, 5 items for Peers).
• Subscale Composition:
  • Communication With Instructors: 7 items (assessing questions during class, office hours attendance, TA engagement, LMS discussions).
  • Communication With Peers: 5 items (assessing out-of-class study discussions, texting, social network messaging, online study groups, shared collaborative documents).
• Response Scale: The items are rated using a 5-item Likert-type scale.
• Scoring Procedures:
  • Items are coded numerically from 1 to 5.
  • Subscale scores are calculated by computing the arithmetic mean or the sum of items corresponding to each subscale.
  • Communication With Instructors Score: Sum of items 1 through 7 (range: 7 to 35) or mean (range: 1.00 to 5.00).
  • Communication With Peers Score: Sum of items 8 through 12 (range: 5 to 25) or mean (range: 1.00 to 5.00).
  • There are no reverse-coded items. Higher scores reflect a higher frequency of engaging in targeted academic communication.

Permissions & Fee and Test Year

The Academic Communication Inventory was officially published in 2023 (print appearance in 2024). The authors, Dr. Kristen A. Archbell and Dr. Robert J. Coplan, developed the instrument to facilitate empirical research in higher education and pedagogical advancement. The scale is non-commercial and available free of charge for non-commercial academic research and teaching purposes. Formal commercial applications, proprietary licensing, or widespread institutional packaging requires permission from the copyright holder and authors. Researchers utilizing the scale are requested to cite the original validation publication in the Canadian Journal of Behavioural Science.

References

• Archbell, K. A., & Coplan, R. J. (2024). Conceptualization and assessment of academic communication among Canadian university students. Canadian Journal of Behavioural Science / Revue canadienne des sciences du comportement, 56(3), 253–264. https://doi.org/10.1037/cbs0000369
• Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman and Company.
• Kuh, G. D. (2009). What student affairs professionals need to know about student engagement. Journal of College Student Development, 50(6), 683–706. https://doi.org/10.1353/csd.0.0099
• Tinto, V. (1993). Leaving college: Rethinking the causes and cures of student attrition (2nd ed.). The University of Chicago Press. https://doi.org/10.7208/chicago/9780226922461.001.0001
• Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.

Items of the Scale