Student Approaches to Learning Scale (SAL / R-SPQ-2F)

Abstract

The Student Approaches to Learning Scale, operationally known in psychometric literature as the Revised Two-Factor Study Process Questionnaire (R-SPQ-2F), is one of the most widely deployed self-report instruments designed to evaluate university students’ orientations toward academic study. Developed by John B. Biggs, David Kember, and Doris Y. P. Leung in 2001, the instrument represents an empirically refined, psychometrically streamlined revision of Biggs’s original 42-item Study Process Questionnaire (SPQ) published in 1987. Grounded in the phenomenographic tradition of student learning research and Biggs’s overarching Presage-Process-Product (3P) Model of teaching and learning, the R-SPQ-2F condenses the measurement of learning processes into two overarching dimensions: the Deep Approach (DA) and the Surface Approach (SA).

Comprising 20 items answered on an authentic 5-point Likert scale (ranging from 1 = this item is only rarely true of me to 5 = this item is always or almost always true of me), the instrument is structured hierarchically. The two main scales are each composed of two 5-item subscales: Deep Motive (DM) and Deep Strategy (DS) for the Deep Approach, and Surface Motive (SM) and Surface Strategy (SS) for the Surface Approach. Over two decades of rigorous international validation across undergraduate, postgraduate, and professional cohorts (such as medicine, engineering, and social sciences) have demonstrated that the R-SPQ-2F exhibits acceptable to excellent internal consistency (Cronbach’s alpha values typically ranging between .72 and .84 for the main scales), robust construct validity confirmed via confirmatory factor analysis (CFA), and compelling predictive validity regarding qualitative academic performance and conceptual understanding.

Keywords

Student Approaches to Learning, R-SPQ-2F, Study Process Questionnaire, Deep Approach, Surface Approach, John Biggs, 3P Model of Teaching and Learning, Higher Education Psychometrics, Constructive Alignment, Educational Assessment

Authors

The Revised Two-Factor Study Process Questionnaire was developed and validated collaboratively by three prominent educational researchers based in Hong Kong:

• John B. Biggs, PhD: Honorary Professor of Psychology at the University of Hong Kong and formerly Professor of Education at the University of Newcastle, Australia. Biggs is internationally recognized for formulating the concept of Constructive Alignment and the Structure of Observed Learning Outcomes (SOLO) taxonomy.
• David Kember, PhD: Professor of Higher Education at the University of Hong Kong and later at the Chinese University of Hong Kong and the University of Tasmania. His scholarship focuses extensively on tertiary curriculum reform, university teaching quality, and longitudinal student learning trajectories.
• Doris Y. P. Leung, PhD: Associate Professor and quantitative psychometrician, affiliated with the School of Nursing and the Educational Development Centre at The Hong Kong Polytechnic University, specializing in applied multivariate statistics, psychometric modeling, and structural equation modeling in health and educational settings.

Purpose

The primary purpose of the R-SPQ-2F is to provide higher education researchers, faculty developers, institutional researchers, and classroom instructors with a parsimonious, theoretically grounded, and psychometrically robust instrument to assess how students interact with their learning tasks. In the late 20th century, the original 1987 SPQ contained 42 items measuring three separate approaches: Deep, Surface, and Achieving, each dissected into motive and strategy components. Over years of empirical utilization, however, researchers identified severe psychometric limitations in the 1987 instrument: the Achieving scale frequently cross-loaded or failed to emerge as an independent latent factor, and its overall length made it cumbersome for contemporary university research and practical classroom diagnostic routines.

Biggs, Kember, and Leung (2001) redesigned the scale to serve two critical purposes:

1. Curriculum and Teaching Evaluation: To evaluate the impact of educational environments, assessment formats, and pedagogical innovations. A teaching environment that promotes constructive alignment, active problem-solving, and formative assessment should theoretically encourage a shift toward deeper learning approaches while suppressing surface strategies.
2. Individual and Cohort Diagnostics: To diagnose cohort-level tendencies or identify individual students who rely predominantly on rote memorization, syllabus limitation, and task minimization due to excessive workload, high anxiety, or misaligned examination systems.

Importantly, the R-SPQ-2F was never designed as an immutable diagnostic test of intellectual ability or an unalterable personality inventory. Rather, it conceptualizes a student’s approach to learning as a dynamic, relational response to the contextual demands of the teaching-learning environment. Consequently, its major research applications include comparative educational research, pre-test/post-test pedagogical intervention studies, the evaluation of blended and flipped classrooms, and large-scale quality assurance reviews across global university contexts.

Psychological Construct

The Student Approaches to Learning (SAL) framework represents a foundational paradigm within educational psychology. Unlike trait-based theories of intelligence or cognitive styles (e.g., field dependence-independence), SAL posits that learning approaches reflect the dynamic interaction between the student’s personal characteristics (intentions, previous knowledge, intrinsic values) and the immediate educational context (assessment designs, teaching styles, curriculum freedom).

1. The Deep Approach (DA)

A Deep Approach to learning is characterized by an intrinsic drive to understand the underlying principles, theoretical frameworks, and broader meanings of academic content. When adopting a deep approach, students do not view educational tasks as external hurdles to be cleared with minimal effort, but rather as opportunities for intellectual engagement and cognitive mastery. The Deep Approach comprises two interrelated psychological facets:

• Deep Motive (DM): Driven by intrinsic curiosity, genuine interest in the subject matter, and the personal satisfaction derived from understanding complex ideas. The learner perceives academic topics as intrinsically engaging, intellectually stimulating, and personally relevant (e.g., “I work hard at my studies because I find the material interesting”).
• Deep Strategy (DS): Characterized by active, self-regulated cognitive strategies. The learner seeks to maximize understanding by relating new information to prior knowledge, examining theoretical arguments critically, integrating concepts across diverse modular courses, testing personal hypotheses, and reading beyond the mandatory curriculum boundaries (e.g., “I test myself on important topics until I understand them completely”).

2. The Surface Approach (SA)

Conversely, a Surface Approach to learning is governed by extrinsic pragmatism, anxiety regarding academic failure, and an imperative to satisfy assessment criteria with minimal expenditure of cognitive effort. The student perceives the academic task as an imposed, external demand that must be managed mechanically. The Surface Approach is subdivided into two operational components:

• Surface Motive (SM): Motivated by an overwhelming desire to avoid failure and obtain institutional qualifications, coupled with a fundamental lack of personal interest in the underlying academic discipline. The dominant psychological objective is academic survival through task minimization (e.g., “My aim is to pass the course while doing as little work as possible”).
• Surface Strategy (SS): Characterized by reproductive cognitive tactics, predominantly rote memorization of discrete facts, syllabus-bound studying, and an exclusive focus on predicted examination questions. The learner avoids conceptual abstraction or synthesis, treating course content as an unintegrated catalogue of isolated facts (e.g., “I learn some things by rote, going over and over them until I know them by heart even if I do not understand them”).

Theoretical Framework

The R-SPQ-2F is rooted in the phenomenographic investigations conducted in Sweden during the mid-1970s by Ference Marton and Roger Säljö (1976), who famously demonstrated that when university students read identical academic texts, their qualitative understandings diverged radically based on their processing orientation. Those adopting a deep approach focused on the author’s primary intention, thematic structure, and underlying logic, whereas those adopting a surface approach focused on isolated words, factual data, and anticipated test questions. This empirical dichotomy was subsequently expanded across higher education institutions in the United Kingdom by Noel Entwistle and Paul Ramsden through the Lancaster Approaches to Studying inventories (such as the Approaches and Study Skills Inventory for Students, or ASSIST).

A crucial theoretical principle underpinning the 3P model is Constructive Alignment. Biggs argued that in an optimally designed educational ecosystem, the institutional intended learning outcomes, the teaching/learning activities, and the assessment tasks are systematically aligned. When assessments reward high-order cognitive processes (synthesis, evaluation, problem-solving), students are structurally encouraged to adopt Deep Approaches. Conversely, when examinations reward unreflective factual recall or impose unreasonable workload demands, the institutional context systematically forces even intellectually capable students to retreat into Surface Approaches.

Validity

The psychometric validity of the R-SPQ-2F has been confirmed through numerous empirical investigations spanning diverse geographic, cultural, and disciplinary landscapes.

1. Construct and Structural Validity

In the seminal validation study by Biggs, Kember, and Leung (2001), administered to an initial cohort of 229 undergraduate students and cross-validated on a comprehensive secondary cohort of 495 students across health sciences, business, and humanities faculties at a Hong Kong university, Confirmatory Factor Analysis (CFA) demonstrated that the revised two-factor hierarchical model possessed superior structural fit compared to alternative 1987 models. The root mean square error of approximation (RMSEA) was .055, and the Comparative Fit Index (CFI) reached .920, confirming that the hypothesized latent architecture reliably mirrors empirical student response patterns.

2. Convergent and Discriminant Validity

Extensive cross-validation has verified the convergent validity of the R-SPQ-2F against parallel psychoeducational instruments:

• Correlations with the ASSIST: Deep Approach scores on the R-SPQ-2F demonstrate strong, statistically significant positive correlations (ranging from r = .68 to .76, p < .001) with the Deep Approach scale of Noel Entwistle’s ASSIST instrument, while the Surface Approach scale correlates strongly with the ASSIST Surface Apathetic subscale (r = .62 to .71).
• Correlations with the MSLQ: Deep Approach scores exhibit significant positive associations with the Metacognitive Self-Regulation (r = .52) and Critical Thinking (r = .58) subscales of the Motivated Strategies for Learning Questionnaire (Pintrich et al., 1991).
• Discriminant Validity: The latent correlation between the Deep Approach and Surface Approach is routinely found to be either moderately negative or statistically orthogonal (typically ranging from r = -.15 to -.38), confirming that Deep and Surface orientations represent distinct, non-overlapping psychological constructs rather than reciprocal endpoints of a single continuum.

3. Predictive and Criterion Validity

The R-SPQ-2F demonstrates robust predictive validity across academic disciplines. Empirical studies consistently demonstrate that Deep Approach scores are positively correlated with higher academic achievement, higher grade point averages (GPA), superior performance on clinical reasoning examinations in medical education, and complex conceptual performance mapped via the SOLO taxonomy. In contrast, elevated Surface Approach scores consistently correlate with higher examination anxiety, test attrition, lower GPA, and a tendency toward superficial cognitive closure.

Reliability

The reliability of the R-SPQ-2F has been rigorously demonstrated through internal consistency and temporal stability metrics across numerous cross-cultural populations.

1. Internal Consistency

In the seminal publication by Biggs, Kember, and Leung (2001), the Cronbach’s alpha internal consistency coefficients for the primary scales were as follows:

• Deep Approach (10 items): α = .73
• Surface Approach (10 items): α = .64

At the 5-item subscale level, the original authors reported: Deep Motive (α = .62), Deep Strategy (α = .63), Surface Motive (α = .72), and Surface Strategy (α = .57). While the subscale alpha values are modest—an inherent psychometric artifact of brief 5-item scales capturing multidimensional behavioral manifestations—the aggregated 10-item composite dimensions exhibit robust reliability.

Subsequent international validation studies have frequently reported even higher internal consistency values. For example, in an extensive European study involving 1,142 university students across the Netherlands and Belgium (Stes et al., 2013), the Deep Approach yielded an alpha of .82, and the Surface Approach yielded an alpha of .78. Validations in Spain (Justicia et al., 2008), the United Kingdom (Phan & Deo, 2007), and Latin America (Freiberg Hoffmann et al., 2017) have similarly documented composite reliability (Raykov’s rho) and Cronbach’s alpha values consistently meeting or exceeding the .75 threshold.

2. Test-Retest Reliability

Evaluating the temporal stability of the R-SPQ-2F requires careful conceptual distinction between an immutable personality trait and a dynamic learning orientation. Because approaches to learning are inherently context-sensitive, stability coefficients are expected to be moderate over prolonged educational transitions. Over short intervals (2 to 4 weeks under identical course conditions), test-retest reliability coefficients range between r = .79 and .85. Over long-term academic terms (6 to 12 months), stability coefficients attenuate to r = .45 to .60, reflecting meaningful, measurable shifts in student learning orientations in response to varying assessment tasks, grading criteria, and pedagogical styles.

Factor Analysis

The empirical foundation of the R-SPQ-2F relies on structural equation modeling (SEM) and confirmatory factor analysis (CFA) designed to resolve historical discrepancies present in Biggs’s 1987 42-item model.

Confirmatory Factor Analytic Models

Biggs, Kember, and Leung (2001) evaluated four competing structural models via maximum likelihood estimation to determine the most parsimonious and psychometrically sound representation of the 20 items:

1. Model 1 (Two-Factor Uncorrelated): Assumed Deep and Surface items loaded onto two orthogonal latent traits without correlation. This model demonstrated poor fit (χ²/df > 4.5, RMSEA > .085, CFI < .80).
2. Model 2 (Two-Factor Correlated): Ten items loaded directly onto a single Deep factor, and ten items loaded onto a single Surface factor, with the two factors correlated. Fit indices improved significantly (χ²/df = 2.45, RMSEA = .061, CFI = .885).
3. Model 3 (Four-Factor First-Order Correlated): The 20 items loaded onto their four designated subscales (DM, DS, SM, SS), allowing all four first-order factors to inter-correlate. This model demonstrated strong empirical fit (χ²/df = 1.98, RMSEA = .053, CFI = .927).
4. Model 4 (Hierarchical Two-Factor Second-Order Model): The 20 items loaded onto their four respective first-order factors (DM, DS, SM, SS), which in turn loaded onto two higher-order latent constructs: Deep Approach and Surface Approach. This hierarchical model yielded excellent statistical parsimony and model fit (χ²/df = 2.04, RMSEA = .055, CFI = .920, TLI = .908, SRMR = .052).

The factor loadings for the items onto their respective subscales in the second-order model were consistently robust, with standardized coefficients typically ranging from .45 to .75. Standardized loadings of the first-order factors onto the second-order approaches were exceptionally high:

• Deep Motive → Deep Approach: γ = .88 to .94
• Deep Strategy → Deep Approach: γ = .85 to .91
• Surface Motive → Surface Approach: γ = .82 to .89
• Surface Strategy → Surface Approach: γ = .79 to .86

This hierarchical factorial validity confirms that while researchers may meaningfully report the four subscale scores for granular diagnostic analysis, collapsing the instrument into the two overarching main scales (Deep Approach and Surface Approach) is psychometrically justified and theoretically optimal.

Instrument / Measurement Tool

The Revised Two-Factor Study Process Questionnaire is structured as follows:

• Instrument Name: Revised Two-Factor Study Process Questionnaire (R-SPQ-2F) / Student Approaches to Learning Scale
• Measurement Paradigm: Self-report Likert questionnaire assessing contextualized student learning orientations
• Target Population: Higher education undergraduate and postgraduate university students
• Total Item Count: 20 items
• Factor Architecture:
  • Deep Approach (DA) Scale: 10 items (Sum of Deep Motive and Deep Strategy)
    • Deep Motive (DM) Subscale: 5 items (Items 1, 5, 9, 13, 17)
    • Deep Strategy (DS) Subscale: 5 items (Items 2, 6, 10, 14, 18)
  • Surface Approach (SA) Scale: 10 items (Sum of Surface Motive and Surface Strategy)
    • Surface Motive (SM) Subscale: 5 items (Items 3, 7, 11, 15, 19)
    • Surface Strategy (SS) Subscale: 5 items (Items 4, 8, 12, 16, 20)
• Authentic Response Format: 5-point Likert scale:
  • 1 = this item is only rarely true of me
  • 2 = this item is sometimes true of me
  • 3 = this item is true of me about half the time
  • 4 = this item is frequently true of me
  • 5 = this item is this item is always or almost always true of me (or A to E)
• Scoring Protocol:
  • Subscale and scale scores are calculated by simple summation of raw item values.
  • Deep Motive (DM): Sum of Items 1, 5, 9, 13, 17 (Score range: 5–25)
  • Deep Strategy (DS): Sum of Items 2, 6, 10, 14, 18 (Score range: 5–25)
  • Deep Approach (DA): DM + DS (Score range: 10–50)
  • Surface Motive (SM): Sum of Items 3, 7, 11, 15, 19 (Score range: 5–25)
  • Surface Strategy (SS): Sum of Items 4, 8, 12, 16, 20 (Score range: 5–25)
  • Surface Approach (SA): SM + SS (Score range: 10–50)
  • Reverse Scored Items: None. All items are positively keyed toward their respective subscale.
• Administration Time: Approximately 5 to 10 minutes.

Permissions & Fee and Test Year

The R-SPQ-2F was published in 2001 in the British Journal of Educational Psychology. In accordance with the explicit intentions of the authors (Biggs, Kember, & Leung, 2001), the instrument was published directly in the academic literature to facilitate widespread, non-commercial educational research, teaching evaluation, and faculty development. It is considered an open-access psychometric instrument for non-commercial academic purposes.

Researchers and higher education institutions are permitted to utilize, translate, and reproduce the 20-item scale for scholarly investigations without purchasing commercial licenses or paying royalty fees, provided that formal academic attribution is given to John Biggs, David Kember, and Doris Y. P. Leung. Any commercial repackaging or integration into proprietary, fee-based assessment software typically requires formal permission from the copyright holder (The British Psychological Society / John Wiley & Sons, Ltd.).

References

Biggs, J. (1987). Student approaches to learning and studying. Australian Council for Educational Research. https://eric.ed.gov/?id=ED308201

Biggs, J. (1996). Enhancing teaching through constructive alignment. Higher Education, 32(3), 347–364. https://doi.org/10.1007/BF00138871

Biggs, J. (1999). Teaching for quality learning at university: What the student does. Society for Research into Higher Education & Open University Press.

Biggs, J., Kember, D., & Leung, D. Y. P. (2001). The revised two-factor Study Process Questionnaire: R-SPQ-2F. British Journal of Educational Psychology, 71(1), 133–149. https://doi.org/10.1348/000709901158433

Entwistle, N., & Ramsden, P. (1983). Understanding student learning. Croom Helm.

Freiberg Hoffmann, A., Stover, J. B., de la Iglesia, G., & Fernández Liporace, M. (2017). Validation of the Revised Two-Factor Study Process Questionnaire (R-SPQ-2F) in Argentinean university students. Revista de Psicodidáctica, 22(1), 38–44. https://doi.org/10.1016/S1136-1034(17)30043-4

Justicia, F., Pichardo, M. C., Cano, F., Berbén, A. B. G., & de la Fuente, J. (2008). The Revised Two-Factor Study Process Questionnaire (R-SPQ-2F): Exploratory and confirmatory factor analyses at Spanish universities. European Journal of Psychology of Education, 23(3), 355–372. https://doi.org/10.1007/BF03173004

Marton, F., & Säljö, R. (1976). On qualitative differences in learning: I—Outcome and process. British Journal of Educational Psychology, 46(1), 4–11. https://doi.org/10.1111/j.2044-8279.1976.tb02980.x

Phan, H. P., & Deo, B. (2007). The revised two-factor Study Process Questionnaire: Assessment of students’ approach to learning via a confirmatory factor analysis. Higher Education Research & Development, 26(3), 275–290. https://doi.org/10.1080/07294360701494297

Pintrich, P. R., Smith, D. A., García, T., & McKeachie, W. J. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). National Center for Research to Improve Postsecondary Teaching and Learning, University of Michigan.

Stes, A., De Maeyer, S., & Van Petegem, P. (2013). Examining the cross-cultural validity of the Revised Two-Factor Study Process Questionnaire (R-SPQ-2F) in European higher education. Studies in Higher Education, 38(6), 890–904. https://doi.org/10.1080/03075079.2011.613503

13. Items of the Scale (Questionnaire)