Session Information
99 ERC SES 04 T (P), Posters
Paper Session
Contribution
This study presents findings from semi-structured interviews with two tutors of the Learning+ program, illustrating how diagnostic assessment data, generated through the Number Interview, informed mathematics tutoring for Year 7 students performing below standard expectations. Using reflexive thematic analysis, three data-driven themes were identified, ordered by their frequency and explanatory power: the diagnostic utility of the Number Interview (what information illuminated students’ mathematical understanding), critical factors in differentiating teaching (how tutors enacted and adapted instruction), and guiding student progression (why particular instructional decisions were made in response to learner needs and program goals). These themes collectively portray tutors’ ongoing cycles of curriculum enactment, the ways they drew on evidence, and the purposes underpinning their decisions, supported by verbatim accounts and analytic vignettes that illustrate theory–practice connections. Theme 1 highlights tutors’ perceptions of the Number Interview as a tool with notable breadth, depth, and adaptability. They valued the multiple grade-banded versions that provided developmental continuity and a clear trajectory of mathematical growth. The adaptive nature of the assessment enabled real-time adjustments, ensuring students were appropriately challenged. Its hierarchical structure functioned as a visual representation of conceptual progression, clarifying next instructional steps in number and early algebra. Implementation guidelines supported consistent administration, and one tutor even reported using adapted versions of the tool outside the Learning+ program because of its diagnostic precision. Although they recognised constraints, particularly limited follow-up probing compared with external assessments such as NAPLAN or TIMSS, and a narrow focus on number, they viewed this focus as pedagogically justified, given the centrality of numeracy to broader mathematical achievement. Extended student responses offered insight into reasoning processes, enabling tutors to select activities that strengthened conceptual understanding while promoting more efficient strategies. Examples included facilitating the transition from additive to multiplicative reasoning using arrays, reinforcing equivalence, and structuring spaced review for durable learning. Theme 2 depicts tutors’ dynamic orchestration of planning, monitoring, and reflection. Instruction was intentionally student-centred, with continual adjustments made in response to observed strategies and indicators of confidence. Correctness, speed, and justification of reasoning served as formative markers of understanding. Tutors accelerated instruction when responses demonstrated fluency and paused when less efficient strategies, such as skip-counting, signalled evolving understanding. They designed tasks aligned with assessment evidence by maintaining the structural features of the Number Interview while varying numerical values, and they layered explicit instruction, visual models, and distributed practice across sessions. Professional learning, including master classes and professional learning communities (PLCs), further strengthened their pedagogical content knowledge and provided a shared framework for refining instructional choices. Their reflections revealed deliberate attempts to build conceptual clarity prior to procedural fluency while maintaining student motivation and confidence. Theme 3 situates tutoring within a broader goal of accelerating student progression. Tutors emphasised the value of flexibility to depart from year-level pacing to address foundational gaps, viewing the one-to-one online format as a unique opportunity. Their responsibilities mirrored those outlined in the Learning+ handbook, including administering diagnostic assessments, planning targeted sessions, communicating progress, and nurturing students’ confidence and self-advocacy. Two engagement contingencies were identified. First, some students initially misunderstood the program’s purpose, expecting homework assistance rather than targeted teaching. Second, motivation varied with some learners embracing challenge, while others were error-averse and required careful support to take intellectual risks. These contingencies shaped goal setting, pacing, and opportunities for consolidation, prompting tutors to balance progression with reassurance and revisit prior understandings to secure equitable continuity of learning for students across the ten-week program. Overall, the analysis provides an empirically grounded account of how diagnostic assessment and differentiated instruction support progression in number and algebra while fostering student efficiency, confidence, and self-advocacy.
Method
This study draws on semi-structured interviews with two Learning+ tutors to examine how the Number Interview, a criterion-referenced diagnostic assessment in number and early algebra, was interpreted and acted in planning and teaching. Prompts invited tutors to describe session structures; review short video excerpts of their tutoring; explain how they read and acted on the Number Interview evidence; and comment on program resources, PLCs, student motivation, goal setting, and perceptions of Learning+ aims. Interviews were audio-recorded and transcribed for analysis. In keeping with the study’s practice orientation, questioning probed concrete decisions (task choice, sequencing, representations) and rationales tied to specific episodes of student work. Analytically, reflexive thematic analysis was employed. Coding proceeded inductively from transcripts, privileging in vivo codes that retained tutors’ phrasing. Content and thematic analysis was conducted on qualitative data analysis software, NVivo version 15. An initial codebook was developed, compared with an AI-assistent (Spark AI) for convergence and divergence, and refined through constant comparison. To respect empirical salience, themes were sequenced by frequency and prominence rather than by a priori pedagogical chronology. The final themes were: diagnostic utility of the Number Interview; critical factors in differentiating teaching; and guiding student progression. Each theme consolidated subcodes concerning monitoring and adjustment, elicitation of reasoning, curriculum alignment and task sequencing, professional learning, program responsibilities, and student engagement contingencies. The analysis privileged tutors’ meaning-making while attending to the interaction between assessment evidence, pedagogical content knowledge, and program affordances. Where relevant, short analytic summaries linked quoted episodes to specific instructional moves. Trustworthiness was supported through thick description with extended quotations, transparency about coding decisions and theme ordering, and analytic memos linking pre-assessment evidence to instructional moves and perceived outcomes. Visual artefacts (coding schemes) communicated analytic structure. Direct quotations were lightly edited for readability while preserving meaning. Given the small, information-rich sample focused on depth rather than breadth, claims are analytic-general, illuminating how diagnostic evidence can inform tutoring decisions in similar intervention contexts rather than estimating prevalence. Ethical practice included de-identification of participants and attention to role relationships given the researcher’s collegial proximity within the program. Reflexivity was maintained through memoing on positionality and by distinguishing descriptive reporting from evaluative commentary; a short audit trail documented coding revisions and theme naming. Procedures adhered to institutional guidelines for secure data handling, storage, and consent. A brief member-check of descriptive summaries ensured accuracy without constraining reflexive interpretation.
Expected Outcomes
Targeted online mathematics tutoring arose where tutors could diagnose precisely, sequence instruction developmentally, and adjust responsively based on strategy use, accuracy, and confidence. The Number Interview functioned as an organising source of evidence, providing clear starting points, surfacing misconceptions, and aligning instructional choices with curriculum expectations and learning progressions. Professional learning and PLCs participation enhanced assessment literacy and mathematical language, which in turn strengthened explicit teaching, selection of tasks, and the transition from additive to multiplicative reasoning using visual models. Tutors’ reflective adjustments, including pacing changes and strategic use of representations, supported movement from fragile methods toward more efficient strategies. Program affordances mattered. The structure legitimised departures from year-level pacing so tutors could address foundational gaps and sustain distributed practice until efficient strategies consolidated. Two tensions warrant attention: resourcing, tutors sometimes desired more built-in follow-up items linked to interview constructs; and scope/communication, the interview’s focus on number aligns with developmental priorities but leaves other strands under-assessed, and some students initially misunderstood the intervention’s purpose as homework help. Addressing these tensions could amplify impact through clearer messaging, supplementary item banks keyed to interview constructs, and explicit onboarding that frames Learning+ as targeted intervention rather than general tutoring. These findings offer an empirically grounded account of data-informed, differentiated instruction that guides progression in a ten-week intervention. It underscores that effective tutoring is not delivering more of the same, but evidence-led orchestration: eliciting thinking, sequencing tasks against a developmental continuum, calibrating support and challenge to motivation and confidence, and communicating progress purposefully. These conclusions prime the study to connect with literature on formative assessment, differentiation, and progression, consider scalable design elements, and outline professional learning that sharpens decision-making where multiple gaps co-occur while sustaining student confidence and agency.
References
Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1), 7–74. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. Braun, V., & Clarke, V. (2020). One size fits all? What counts as quality practice in (reflexive) thematic analysis? Qualitative Research in Psychology, 18(3), 328–352. https://doi.org/10.1080/14780887.2020.1769238 Byrne, D. (2022). A worked example of Braun and Clarke’s approach to reflexive thematic analysis. Quality & Quantity, 56, 1391–1412. https://doi.org/10.1007/s11135-021-01182-y Department for Education. (2021). Learning+ tutor handbook. Government of South Australia. Dweck, C. S. (2006). Mindset: The new psychology of success. Random House. Griffin, P. (2018). Assessment for learning: An action guide for school leaders. Corwin Press. McAllister, M., & McKinnon, J. (2009). The Griffith University Affective Learning Scale: Confirmatory factor analysis. Nurse Education Today, 29(3), 276–282. Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54–67. https://doi.org/10.1006/ceps.1999.1020 Tomlinson, C. A. (2001). How to differentiate instruction in mixed-ability classrooms (2nd ed.). ASCD. Tomlinson, C. A. (2014). The differentiated classroom: Responding to the needs of all learners (2nd ed.). ASCD.
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