A Drawer-Type Tablet Charging Cart for K-12 Digital Learning Infrastructure: Human-Centered Engineering Design, Opportunity Scoring, and Prototype Validation

Abstract

Managing classroom tablets involves more than electrical charging; it also requires repeated retrieval and return, storage, plug alignment, custody, and queue control. This article presents the human-centered engineering design and field validation of a drawer-type tablet/laptop charging cart for kindergarten-to-grade-12 digital learning infrastructure. Its main contribution is a bilateral drawer-access architecture that converts a conventional front-door, single-queue cabinet into a two-sided parallel-handling product, with design decisions linked to observed school workflows through Lean Product and Process Development, jobs-to-be-done inquiry, opportunity scoring, competitor benchmarking, product-essence mapping, and prototype testing. Field observations at three schools identified six critical handling events; effective storage with reduced queueing was the highest-priority opportunity (importance = 8.6, satisfaction = 5.7, opportunity score = 11.5). Among four access concepts, the drawer-type concept achieved the shortest handling time (4.4 s/device), outperforming front-opening fixed-shelf (7.2 s/device), front-opening movable-rack (8.2 s/device), and top-opening (6.8 s/device) concepts. In classroom validation, average handling time decreased from 10.9 to 4.8 s/device, and throughput increased from 5.5 to 12.5 devices/min. These design-stage, descriptive results indicate that bilateral drawer access can reduce serial queueing while preserving storage, charging, and custody functions. They support prototype refinement rather than population-level causal inference.

1. Introduction

Digital learning in schools increasingly depends on the reliable circulation, charging, storage, and maintenance of mobile devices. Timotheou et al. [1] showed that digital technologies affect not only student learning outcomes but also school routines, stakeholders, and institutional capacity. Dorris et al. [2] reviewed mobile-device use in primary school classrooms and emphasized that classroom effects depend on the conditions under which devices are implemented. Lohr et al. [3] further showed that support conditions, internet speed, and device-ownership arrangements influence how digital learning is enacted. These studies imply that educational technology adoption is inseparable from the physical and organizational infrastructure that keeps devices ready for use.

Most educational-technology research emphasizes pedagogy, learning applications, or digital competence. By contrast, the mechanical artifacts that organize daily device circulation are rarely treated as engineering design problems. A tablet charging cart is often specified by device capacity, locking type, electrical input, or cabinet dimensions; however, its classroom performance depends on a human–machine interaction sequence that includes queue formation, access direction, door opening, body posture, slot visibility, plug alignment, cable routing, and custody. If this sequence is poorly designed, instructional time can be lost before any digital learning activity begins.

This study frames the charging cart as a human-centered mechanical product and task-support artifact. Gregoriades and Sutcliffe [4] argued that functional requirements should be connected explicitly to the tasks that human agents must perform. Gaiardelli et al. [5] described product-service systems as configurations in which value emerges from interactions among products, users, and service routines. Fang et al. [6] demonstrated that user-centered collective design can guide smart product-service systems, while Peters et al. [7] emphasized that product development is strengthened when users participate as sources of design knowledge rather than as passive recipients. These arguments justify treating charging-cart design as a task-support and product-architecture problem.

Lean Product and Process Development is relevant because it emphasizes front-end knowledge creation, problem definition, cross-functional communication, and waste reduction before product decisions are locked in. Cukor Kirinić and Hegedić [8] identified recent lean product-development trends toward sustainability, digitalization, and broader implementation contexts. Jaffré et al. [9] showed that lean product-development barriers and success factors are context-dependent rather than universal. Islam [10] reported that lean product development can support sustainable operational performance in new production-system introduction. Treviño-Elizondo et al. [11] connected lean and Industry 4.0 maturity, and Mezher et al. [12] interpreted Lean 4.0 as a socio-technical configuration. For a school charging cart, the same alignment is operational: product architecture must support how students, teachers, and support staff actually handle devices.

The present research combines Lean Product and Process Development with jobs-to-be-done inquiry and outcome-driven opportunity scoring. Nam et al. [13] demonstrated that outcome-driven innovation can transform customer outcomes into prioritized opportunity areas. Gille [14] showed that manual-handling cart design should consider the mechanical forces and conditions that shape user effort. Hefter et al. [15] used participatory human-factors design to redesign supply carts and improve workflow access in a healthcare setting. Lamé et al. [16] argued that design expertise can function as a quality-improvement strategy. At the methodological-foundation level, the workflow also draws on Morgan and Liker’s account of the Toyota Product Development System [17] and Ward and Sobek’s lean product and process development framework [18]. The jobs-to-be-done perspective is grounded in Christensen et al.’s theory of customer choice [19], and the opportunity-scoring logic follows Ulwick’s jobs-to-be-done and outcome-driven innovation formulation [20]. Stakeholder inquiry, personas, and design communication are further aligned with service-design practice as described by Stickdorn et al. [21]. Together, these studies and methodological foundations support a research position in which a charging cart is evaluated through observed tasks, prioritized opportunity scores, product architecture, and field performance rather than through nominal capacity alone.

Against this background, the novelty of this study is twofold. First, the article proposes a bilateral drawer-type access architecture that converts a conventional front-door, single-queue cabinet into a two-sided parallel handling artifact while retaining storage, charging, and custody functions. Second, the article demonstrates a reproducible design-validation workflow linking contextual inquiry, opportunity scoring, competitor benchmarking, product essence mapping, A3 synthesis, comparative concept testing, and classroom field validation. The contribution is therefore framed as a stand-alone engineering-design article that tests how a specific product architecture can improve K-12 device-handling performance.

The research objective is to design and validate a drawer-type tablet/laptop charging cart that improves classroom handling efficiency without sacrificing storage capacity, charging function, security, or classroom compatibility. The study makes three contributions. First, it provides empirical evidence of device-handling bottlenecks in K-12 school settings. Second, it describes a reproducible method for translating observed bottlenecks into quantified opportunities and product requirements. Third, it provides prototype evidence showing how bilateral drawer access can reduce average handling time, increase throughput, and maintain positive user satisfaction in routine classroom use.

2. Materials and Methods

2.1. Research Design and Case Context

The study adopted an exploratory mixed-methods engineering design approach with an embedded prototype-validation stage. The unit of analysis was the product architecture and handling workflow of classroom tablet/laptop charging carts. Empirical work was conducted in Taiwanese K-12 educational settings where classroom tablets were already used in routine school activities. The article is reported as a stand-alone product-innovation study. The process diagrams, prototype photographs, and descriptive datasets presented in the article were generated during the engineering design and validation work reported here.

The study was designed as an applied engineering design case with field-informed prototype validation, rather than as a randomized controlled trial. Accordingly, the evidentiary standard is exploratory and design-oriented. Field observations, opportunity scoring, concept-level timing, and post-use satisfaction ratings were triangulated to determine whether the bilateral drawer-access architecture was sufficiently promising for further engineering development.

Three school sites were included. Site A was an elementary school where a class-level charging cart was placed inside the classroom, and pupils were expected to retrieve and return their own tablets. Site B was a senior high school where devices were managed by an information center and transported by assigned students. Site C was a high school where device management was organized through a library-based system and supported by dedicated staff. The sites were anonymized to protect participants, school operations, and institutional routines.

Participant numbers were constrained by authentic school operation, site access, and prototype availability. The samples should therefore be interpreted as design-stage samples suitable for identifying use problems, prioritizing design opportunities, and validating prototype feasibility. They were not intended to function as statistically powered samples for generalizing the results to all K-12 classrooms.

2.2. LPPD-JTBD/ODI Workflow

The workflow followed the Lean Product and Process Development learning cycle of Look, Ask, Model, Discuss, and Act and was implemented as a design-research sequence. The Look phase documented authentic device-handling tasks; the Ask phase converted critical events into personas and paired importance-satisfaction questions; the Model phase translated evidence into product requirements; the Discuss phase used A3 synthesis to compare alternatives and manage design risks; and the Act phase produced and validated a full-scale prototype. Figure 1 summarizes the design-to-validation logic, while

Table 1. Research design, participants, and outputs across study stages.

Stage	Methods and Data	Sample/Material	Purpose	Output
Look	Contextual inquiry and short on-site interviews	3 school sites	Observe workflows, posture, queueing, visibility, access direction, and spatial constraints.	Six critical events and workflow bottlenecks
Ask	Personas and ODI questionnaire	14 respondents: 7 students, 6 teachers, 1 IT staff	Prioritize user outcomes through importance-satisfaction gaps.	Ranked opportunity areas
Model	Competitor specification and review benchmark	4 commercial charging carts; 62 user reviews	Translate market evidence into requirements and design risks.	Benchmark requirements and review themes
Discuss	Product essence map and A3 synthesis	Four access concepts	Compare product architectures and identify stability/cable-management risks.	Selected drawer-type architecture
Act	Concept testing and classroom validation	Concept test: 18 or 11 participants by concept; field validation: 16 pupils	Measure handling performance and post-use satisfaction.	Validated full-scale prototype

identifies the data source, sample/material, decision purpose, and output of each stage.

Table 1 summarizes the operational protocol of the study by linking each design stage to its data source, decision purpose, and subsequent output. The sequence was cumulative: Contextual inquiry first identified critical handling events; the opportunity questionnaire then prioritized these events; competitor benchmarking translated market evidence and user-review themes into secondary requirements; product-essence mapping and A3 synthesis supported the selection of the drawer-type architecture; and prototype testing generated validation evidence. In this sense, Table 1 functions as a methodological bridge between field observation, design decision-making, and empirical prototype validation rather than as a general project-management summary.

The opportunity-scoring sample consisted of 14 experienced users and stakeholders and was used to prioritize design opportunities derived from field observations. It was not intended to validate a psychometric scale. Likewise, the concept-testing and classroom-validation samples were used to compare observable handling performance under prototype-use conditions. Because the participants were not randomly assigned and the sample sizes were not equal across all concepts, the study reports descriptive design-validation evidence and does not claim inferential hypothesis testing.

2.3. Data Collection Instruments

Contextual inquiry was conducted through structured field notes, photographs, short on-site interviews, and task-sequence observation. The observation checklist covered device location, access direction, door opening, queue formation, body posture, lighting and visibility, plug alignment, cable handling, locking behavior, transport conditions, and surrounding spatial constraints. Observation records were coded as critical events when repeated actions produced waiting time, additional postural demand, collision risk, reduced visibility, plug-alignment difficulty, or custody concerns. The resulting critical events were then reviewed in relation to four stakeholder roles: elementary pupils, secondary students, classroom teachers, and information-management staff. These personas were used as design communication tools to represent different operational perspectives, rather than as statistical categories.

The opportunity questionnaire translated the six observed critical events into paired importance and satisfaction items measured on a 10-point scale. Respondents included students, teachers, and information-technology support staff with direct experience using or managing charging carts. After opportunity scoring, competitor benchmarking was conducted using four commercial carts in the 24–32-device range. Publicly available product specifications were used to compare capacity, device compatibility, access mode, material, and mass. In addition, 62 online user-review comments were coded into positive and negative product-attribute themes so that market expectations and recurring complaints could be incorporated as secondary design constraints rather than treated only as anecdotal background information.

The questionnaire was a project-specific outcome-rating instrument derived from the six field-observed critical events. It was reviewed by the design team for wording consistency, relevance to stakeholder experience, and alignment with the observed handling tasks; however, it was not independently validated as a psychometric scale. The 62 online review comments used in the competitor benchmark were coded according to recurring product attributes, including sturdiness, assembly, locking quality, wheel quality, slot spacing, and cable routing. The coding results were checked through team discussion to support requirement translation, although a formal inter-rater reliability coefficient was not calculated. This evidence was therefore used for design prioritization and requirement development rather than for statistical scale validation.

2.4. Measures and Equations

Opportunity scores were calculated using the outcome-driven opportunity algorithm shown in Equation (1). For critical event $I$, $I_i$denotes the mean importance score, ${ S}_i$denotes the mean satisfaction score, and ${OPP}_i$ denotes the opportunity score. Both $I_i$and${ S}_i$were measured on a 10-point scale.

$${OPP}_i=2I_i-S_i=I_i+\left(I_i+S_i\right)$$

(1)

In this formulation, a larger opportunity score is produced when an outcome is considered important but current satisfaction is relatively low. In this study, ${OPP}_i$ > 10 was used as an operational screening rule for identifying priority opportunity areas in the front-end design process. Scores below 10 were interpreted as secondary or constraint-related requirements when the corresponding events affected safety, custody, compatibility, or product acceptance. Therefore, the threshold should be understood as a design-prioritization rule for this applied engineering project, rather than as a universal statistical cut-off.

Handling performance was calculated using Equation (2), where $T$denotes total session time in seconds, $n$ denotes the number of devices handled during the session, and $t_{avg}$ denotes average handling time per device.

$$t_{avg}=T/n$$

(2)

Throughput was calculated using Equation (3), where $q$ denotes the number of devices handled per minute.

$$q={\displaystyle \frac{60}{t_{avg}}}$$

(3)

Descriptive percentage change was calculated using Equation (4), where x_{baseline} denotes the baseline value and x_{prototype} denotes the prototype value.

$$Change (\%)={\displaystyle \frac{x_{prototype }-{ x}_{baseline}}{x_{baseline}}}\times 100$$

(4)

For handling time, a negative percentage change indicates improvement because a lower value is desirable. For throughput and satisfaction, a positive percentage change indicates improvement because higher values are desirable.

Because the classroom validation used aggregate session records and different cohort sizes in the baseline and prototype sessions, the analysis was descriptive rather than inferential. The equations were used to make the design comparison transparent, reproducible, and interpretable, not to claim population-level statistical inference. The available dataset contained aggregate session totals, concept-level totals, and satisfaction item means. Accordingly, analysis of variance, mixed-effects modeling, confidence intervals based on participant-level repeated trials, and reliability statistics were not appropriate for the present dataset. The analysis therefore reports descriptive statistics only and avoids causal or population-level claims.

2.5. Validation Model and Key Indicators

The validation model was derived from the highest-ranked opportunity area and the secondary design constraints identified through field inquiry, opportunity scoring, and competitor benchmarking. The central design hypothesis was that bilateral drawer access could transform a conventional single-queue retrieval sequence into two parallel access lanes, thereby reducing handling time while preserving device capacity, charging readiness, and custody functions. The validation model therefore combined performance indicators with user-acceptance and requirement-preservation indicators, rather than relying on a single usability measure.

Five indicators were used to evaluate the prototype. The first indicator was opportunity priority, measured by ${OPP}_i$, which identified the critical handling event that justified design intervention. The second was concept-level handling efficiency, measured by average handling time per device ($t_{avg}$) and throughput ($q$) across four access concepts. The third was classroom field performance, measured by the baseline-to-prototype change in average handling time and throughput under routine classroom use. The fourth was user acceptance, measured through post-use satisfaction ratings on a five-point scale. The fifth was requirement preservation, assessed descriptively through storage capacity, lockability, anti-tip logic, cable-routing feasibility, device compatibility, and compatibility with classroom furniture scale.

This indicator structure connected the front-end opportunity score to the product architecture and then to prototype-level evidence. In other words, the validation model did not evaluate the drawer-type cart only as an isolated object; it evaluated whether the proposed access architecture responded to the observed school workflow, improved handling performance, and maintained the functional requirements expected of a classroom charging cart.

2.6. Methodological Scope, Controls, and Engineering Validation Boundary

To define the evidentiary scope of the study, the validation design distinguished among three levels of evidence. First, contextual inquiry and opportunity scoring provided problem-discovery evidence by identifying and prioritizing field-observed handling bottlenecks. Second, comparative concept testing provided design-screening evidence by comparing four access architectures under prototype-use conditions. Third, classroom validation provided field-feasibility evidence by testing the fabricated drawer-type prototype in a routine school setting. These three levels of evidence support engineering design decision-making, but they do not establish a statistically generalizable treatment effect.

Before concept testing and classroom validation, users received a brief standardized explanation of the access procedure. The sessions were timed as complete handling events using stopwatch and video-assisted field records, rather than as repeated participant-level trials. The timing results were therefore normalized as seconds per device and devices per minute. Measurement uncertainty, user fatigue, handedness, individual learning effects, and queue-density variation were not statistically modeled in the present dataset.

The engineering validation was limited to prototype feasibility. The drawer-type prototype incorporated a one-drawer-at-a-time anti-tip logic as a design precaution; however, the study did not conduct finite element analysis, dynamic stability testing, formal drawer-load certification, thermal distribution modeling, charging-temperature monitoring, vibration testing, lifecycle durability testing, or electrical safety certification. These boundaries are stated explicitly because they represent required tasks for product certification, procurement qualification, and future engineering research. Accordingly, the present study should be interpreted as a design-stage prototype validation that demonstrates feasibility and design promise, rather than as final certification of mechanical, thermal, electrical, or long-term durability performance.

3. Results

3.1. Field-Observed Bottlenecks and ODI Prioritization

The field inquiry showed that charging-cart performance was constrained by a cluster of interacting use problems rather than by charging electronics alone. At Site A, 22 pupils queued at a front-opening cart to retrieve or return tablets, requiring approximately 240 s in total, or 10.9 s/device. At Sites A and B, lower storage rows required bending or squatting, while front-door access and partially enclosed storage reduced visibility during plug alignment. At Site C, the support staff emphasized that initial cable routing and locking quality affected maintenance and custody confidence.

Six critical events were extracted from the field observations: prolonged queueing, inadequate locking and custody, side-space occupation during access, awkward squatting or bending, difficult plug alignment, and collisions or handling disturbance during device distribution or return.

Table 2. ODI opportunity scores for the six critical events.

Critical Event	Importance (I)	Satisfaction (S)	OPP = 2I − S	Interpretation
Effective storage and reduced queueing time	8.6	5.7	11.5	Underserved priority
Reliable locking and custody	8.6	8.6	8.6	Secondary; adequately served
Reduced side-space occupation during access	5.7	6.4	5.0	Low priority/over-served
Reduced squatting or bending during access	5.0	5.0	5.0	Low priority
Easier plug alignment during return	8.6	7.9	9.3	Secondary opportunity
Fewer collisions during distribution and return	7.9	7.1	8.7	Secondary opportunity

reports the paired importance and satisfaction values for these events, together with the resulting opportunity scores. Effective storage with reduced queueing generated the highest opportunity score (OPP = 11.5), indicating the most underserved design opportunity and confirming queue reduction as the primary target for architectural intervention.

Although easier plug alignment (OPP = 9.3), fewer collisions during distribution and return (OPP = 8.7), and reliable locking and custody (OPP = 8.6) did not exceed the priority threshold, they were retained as secondary design requirements because they directly affected user acceptance, device protection, and school custody expectations. Reduced side-space occupation and reduced squatting or bending received lower scores and were therefore treated as lower-priority issues, although they remained relevant to overall usability. Figure 2 visualizes the prioritization results and shows how the opportunity-scoring procedure separated the primary intervention target from secondary and constraint-related requirements.

3.2. Competitor Benchmark and Requirement Translation

The competitor benchmark showed that the sampled market was dominated by front-opening cabinet architectures. All four benchmarked products used either single- or double-front-door access, and none adopted a lateral drawer-access strategy. As summarized in

Table 3. Competitor benchmark of commercial charging carts in the 24–32 device range.

Product Code	Slots	Device Compatibility	Access Mode	Material	Mass (kg)	Review Count
E	32	Mixed laptops/tablets/netbooks	Single front door	Steel/plastic	36.3	32
T	32	Up to 16-inch Chromebooks/laptops	Double front door	Alloy	113.4	12
L	24	Chromebooks/laptops	Double front door	Alloy/plastic	45.4	10
P	24	Up to 15-inch laptops	Double front door	Alloy	44.0	8

, this finding established the baseline market configuration against which the proposed drawer-type architecture was evaluated. The benchmark also defined boundary conditions for the new design, including the 24–32-device capacity range, tablet/laptop compatibility, cabinet mass, and material patterns. On this basis, the study retained a 32-device target while treating access mode as a potential differentiation variable rather than as a fixed market convention.

The review analysis further clarified the implementation constraints that the new product architecture needed to preserve. Across 62 user-review comments, the most frequent positive themes were product sturdiness (19%), easy assembly (15%), suitable capacity (15%), wheel mobility (9%), and combination or code locking (8%). The most frequent negative themes were time-consuming assembly (14%), shipping damage (12%), poor locking quality (12%), poor wheel quality (10%), insufficient slot spacing (10%), and messy cable routing (7%).

Table 4. Requirement translation from field inquiry, ODI, and competitor benchmarking.

Design Requirement	Evidence Source	Target or Design Response
Reduce queueing and handling time	Highest ODI score; baseline classroom handling time	Use bilateral drawer access to enable two-sided parallel handling; target < 5 s/device
Maintain sufficient device capacity	Competitor benchmark and school class size	Provide 32 slots for tablets/laptops up to approximately 14 inches
Improve plug alignment and visibility	Contextual inquiry and secondary ODI opportunity	Use open drawer access, angled dividers, and visible charging-port orientation
Preserve custody and stability	Competitor review complaints and school management needs	Use lockable drawers and one-drawer-at-a-time anti-tip logic
Simplify cable routing and maintenance	Support-staff feedback and competitor review complaints	Route cables inside drawers and avoid rear-only maintenance operations
Fit classroom furniture scale	Site observation and product benchmark dimensions	Maintain compact cabinet dimensions and mobile wheel base

translates these benchmark and review findings into product requirements. This translation step was important because the opportunity score identified queueing as the primary design target, whereas the benchmark evidence showed that capacity, lockability, cable routing, wheel mobility, and assembly quality remained necessary conditions for product adoption. Therefore, the drawer-type concept was not evaluated only as a faster access mechanism; it was required to improve handling efficiency while preserving the functional and implementation requirements expected of classroom charging carts.

3.3. Product Essence Map and Drawer-Type Architecture

The product essence map in Figure 3 served as an intermediate design-translation artifact that linked user outcomes to controllable product-architecture variables. Rather than treating handling efficiency as a single isolated feature, the map decomposed this outcome into several design variables: access direction, number of simultaneous access lanes, slot visibility, divider geometry, cable-routing path, and anti-tip behavior. This decomposition clarified how the observed workflow bottlenecks could be addressed through physical product architecture.

Figure 3 also explains the rationale for selecting the drawer-type architecture. Bilateral lateral access was expected to reduce queueing by transforming a conventional single serial line into two parallel handling lanes. Angled dividers and open drawer visibility were expected to improve plug alignment during device return. Internal cable routing was used to simplify maintenance and reduce cable disorder, while the one-drawer-at-a-time logic was incorporated to preserve stability during access. The resulting design hypothesis was that bilateral drawer access could improve handling efficiency while maintaining the storage, charging, custody, and stability functions required of a mobile classroom charging cart.

3.4. Prototype Specification and Comparative Concept Testing

The selected prototype adopted a two-drawer cabinet configuration with bilateral internal access zones. The fabricated prototype measured approximately 925 mm × 550 mm × 865 mm (width × depth × height), accommodated 32 devices, and used adjustable dividers to support compatibility with different tablet and laptop sizes. The principal architectural change was the separation of device access from the conventional front-door cabinet sequence. Instead of requiring users to queue in front of a single access face, the drawer-type configuration enabled lateral access from both sides of the cart while keeping the storage, charging, and custody functions within one mobile cabinet. Figure 4 shows the fabricated prototype and its key structural features, including the dual lateral-access drawers, adjustable dividers, and full-scale cabinet implementation.

Comparative concept testing indicated that the drawer-type architecture was the only access concept that met the target of less than 5 s/device. The drawer-type concept achieved an average handling time of 4.4 s/device and a throughput of 13.5 devices/min. Relative to the front-opening fixed-shelf concept, the drawer-type concept reduced average handling time by 38.9%. Relative to the front-opening movable-rack concept, it reduced average handling time by 46.3%.

Table 5. Comparative concept test results.

Access Concept	N	Total Time (s)	Average Time/Device (s)	Throughput (Devices/Min)	Meets < 5 s Target?
Front-opening fixed shelf	18	130	7.2	8.3	No
Front-opening movable rack	18	148	8.2	7.3	No
Drawer-type	18	80	4.4	13.5	Yes
Top-opening	11	75	6.8	8.8	No

and Figure 5 summarize the concept-level handling comparison across the four access architectures.

These concept-test results should be interpreted as descriptive design-screening evidence. The top-opening concept had a smaller sample because of prototype availability and field scheduling constraints. Therefore, the comparison was not designed as a balanced controlled experiment. The values in Table 5 are used to identify the most promising product architecture for further prototype validation, rather than to support inferential statistical claims.

3.5. Classroom Field Validation and Satisfaction

The classroom field validation at Site A applied the validation model defined in Section 2.5. The primary performance indicators were average handling time per device and throughput. In the baseline session, the front-opening cart handled 22 devices in 240 s, corresponding to 10.9 s/device and 5.5 devices/min. In the prototype session, the drawer-type cart handled 16 devices in 77 s, corresponding to 4.8 s/device and 12.5 devices/min. This represented a 55.9% reduction in average handling time and a 126.7% increase in throughput.

Table 6. Classroom field-validation performance based on aggregate session records.

Metric	Baseline Front-Opening Cart	Drawer Prototype	Descriptive Change
Devices handled in session	22	16	-
Total session time (s)	240	77	-
Average time per device (s)	10.9	4.8	−55.9%
Throughput (devices/min)	5.5	12.5	+126.7%

and Figure 6 summarize these before–after results based on aggregate classroom session records.

Because the baseline and prototype sessions involved different cohort sizes, the field validation is interpreted as descriptive feasibility evidence rather than as a controlled experimental effect. The purpose of Table 6 and Figure 6 is therefore to show whether the prototype met the practical handling-efficiency target under classroom-use conditions, not to claim that the result can be statistically generalized to all classrooms.

Before using the prototype, participants received a brief standardized demonstration of the drawer-access procedure. The validation measured total session time from the beginning of the retrieval/return sequence to the completion of device placement. The total time was then normalized as average seconds per device and devices per minute. The trial was not repeated in randomized order, and individual-level timing data were not collected. These design choices are reported as limitations of the present design-stage validation.

Post-use satisfaction was positive across all measured items, and Figure 7 shows how users evaluated different aspects of the validation model. The highest scores were for reliable locking/security (4.81/5), preference for drawer storage (4.69/5), effective storage with reduced queueing (4.56/5), and improved appearance (4.56/5). These results suggest that users accepted the drawer-type architecture not only because it improved handling speed, but also because it preserved custody-related functions and perceived product quality.

The secondary requirement items were also positively evaluated. Easier plug alignment scored 4.38/5, and reduced collisions scored 4.19/5, supporting the design requirements derived from opportunity scoring and competitor benchmarking. The lowest mean score was reduced need to squat or bend (4.06/5). Although still positive, this result indicates that future iterations could further improve ergonomic performance through height adjustment, drawer-position balancing, or differentiated upper/lower drawer layouts. Overall,

Table 7. Post-use satisfaction ratings for the drawer prototype (5-point scale, N = 16).

Item	Mean Score
Reliable locking/security	4.81
Preference for drawer storage	4.69
Effective storage and reduced queueing	4.56
Improved appearance	4.56
Easier plug alignment	4.38
Reduced collisions	4.19
Reduced need to squat/bend	4.06

and Figure 7 provide user-acceptance evidence that complements the handling-time and throughput results.

3.6. Engineering Verification Boundary

Table 8. Engineering validation boundary and future verification requirements.

Validation Domain	Status in the Present Study	Future Verification Requirement
Participant number and statistical validity	N = 14 for opportunity scoring, 18/18/18/11 for concept screening, and N = 16 for classroom satisfaction; the study was not powered for inferential testing.	The evidence is interpreted as descriptive design-stage evidence. Future work should use larger multi-school samples, balanced groups, repeated trials, and participant-level timing.
Questionnaire validation and OPP threshold	The ODI instrument was project-specific and derived from field critical events; OPP > 10 was used as an operational screening threshold.	OPP is treated as a design-prioritization index rather than as a validated psychometric or statistical threshold. Future studies should validate the instrument with larger samples.
Timing, training, and measurement accuracy	Users received a brief demonstration; aggregate session timing was used; repeated participant-level timings were not collected.	The results are reported as normalized seconds/device and throughput only. Future experiments should use randomized order, repeated trials, video coding, and observer agreement checks.
Observer bias and review coding	Review comments were coded by recurring product-attribute themes and checked during team discussion; no formal inter-rater reliability coefficient was calculated.	Future studies should use independent coders and report Cohen kappa or an equivalent reliability statistic.
User/device variability and ergonomics	Device sizes and weights, left-/right-handed use, fatigue, queue density, and motion trajectories were not experimentally controlled; posture was observed qualitatively.	RULA/REBA assessment, motion tracking, fatigue analysis, and queue-density sensitivity analysis are future validation tasks.
Mechanical safety and stability	The prototype used a one-drawer-at-a-time anti-tip logic; center-of-gravity shift, maximum allowable drawer moment, rail finite element analysis, dynamic stability, and vibration testing were not performed.	Prototype feasibility is separated from certification-level mechanical validation. Future work should test load capacity, drawer moment, center-of-gravity envelope, rail stress, and transport stability.
Wheel, rail, load capacity, durability, and MTBF	The prototype used production-style cart components, but formal wheel specifications, drawer load rating, lifecycle durability, and mean-time-between-failure estimates were not established.	These are required product-engineering tests before commercialization or procurement specification.
Thermal and electrical safety	Thermal buildup, charging temperatures, thermal distribution, and electrical safety certification were not evaluated in this design-stage study.	No electrical-safety or thermal-certification claim is made. Future work should include temperature monitoring, thermal modeling, overload testing, and applicable safety certification.
Queueing model and class-size sensitivity	The study measured observed handling time and throughput but did not build a discrete-event queueing model or class-size sensitivity model.	Future work should use discrete-event queueing simulation and throughput sensitivity analysis across different class sizes and queue densities.

summarizes the engineering and experimental boundaries of the prototype validation. It distinguishes the claims supported by the present design-stage evidence from the additional verification work required for certification-level product qualification, procurement specification, and broader deployment. The timing data, opportunity scores, satisfaction ratings, and prototype observations support feasibility assessment and design refinement of the drawer-type architecture. However, mechanical safety, thermal behavior, electrical safety, ergonomic performance, lifecycle durability, and statistical generalizability require further controlled testing before the design can be treated as a certified or broadly generalizable product solution.

4. Discussion

The results indicate that a school charging cart should be understood as a human–machine interaction artifact rather than merely as a storage cabinet or electrical accessory. The main performance improvement came from reorganizing the product-access architecture. Conventional front-opening cabinets require users to form a single serial queue and reach into a partially enclosed storage volume. By contrast, the drawer-type prototype created two lateral access zones, improved slot visibility, and shortened the device-handling sequence. This architectural change explains why the drawer-type concept met the target of less than 5 s/device in concept testing and reduced classroom handling time during field validation.

The findings extend recent research on digital learning infrastructure by drawing attention to the physical conditions that support device readiness. Timotheou et al. [1] showed that digital technologies influence not only learning outcomes but also institutional capacity and school routines. The present study complements that perspective by showing that device circulation, charging access, and storage workflow are part of the infrastructure that enables digital learning. Dorris et al. [2] emphasized that mobile-device implementation in primary classrooms depends on implementation conditions, and the present results identify charging-cart access as one such condition. Lohr et al. [3] highlighted school support, internet speed, and device-ownership arrangements as important conditions for active digital learning. This article adds that device readiness, storage access, and handling flow are also practical support conditions that can affect classroom technology use before instruction even begins.

The study also contributes to human-centered and socio-technical design by showing how task-support requirements can be translated into mechanical product architecture. Gregoriades and Sutcliffe [4] argued that system requirements should be connected to the tasks that human agents must perform. In the present study, queueing time, plug alignment, posture, visibility, and custody were translated into design requirements and then into a drawer-type architecture. Gaiardelli et al. [5] described product-service-system value as interactional; this view is reflected in the interaction among the charging cart, students, teachers, devices, and classroom routines. Fang et al. [6] emphasized user-centered collective design for smart product-service systems, and Peters et al. [7] argued for user-driven product development. In this study, contextual inquiry, stakeholder personas, and classroom validation served this role by allowing design decisions to be informed by observed use rather than by assumed product features.

The results further clarify the role of Lean Product and Process Development in applied engineering design. Cukor Kirinić and Hegedić [8] showed that lean product-development research is increasingly connected with sustainability, digitalization, and broader implementation contexts. Jaffré et al. [9] argued that lean product development should be configured according to context rather than applied as a fixed checklist. Islam [10] reported that lean product development can support operational performance when it is connected to implementation needs. Treviño-Elizondo et al. [11] linked lean thinking with Industry 4.0 maturity, while Mezher et al. [12] interpreted Lean 4.0 as a socio-technical configuration. The present study demonstrates a context-specific application of these ideas: the Look–Ask–Model–Discuss–Act workflow generated design knowledge, and the A3 process connected the opportunity score, product essence map, prototype risks, and validation indicators.

The opportunity-scoring results show why prioritization was necessary. Several problems were visible in the field, including awkward posture, locking and custody concerns, plug-alignment difficulty, side-space occupation, and transport disturbance. However, only effective storage with reduced queueing exceeded the opportunity threshold. Nam et al. [13] demonstrated that outcome-driven innovation can rank underserved opportunities; the present study applies this principle to a tangible educational infrastructure product. The lower-scoring issues were not discarded. Instead, they became secondary requirements that the final architecture had to preserve. The drawer-type cart therefore needed to be faster while also remaining lockable, stable, compatible with classroom furniture, and manageable for cable routing.

The competitor benchmark strengthens the design contribution by showing that the proposed architecture differs from the sampled market configuration. Table 3 showed that the benchmarked products were dominated by front-opening cabinet access, while Table 4 translated review themes into product requirements. Customer reviews praised sturdiness and capacity but criticized assembly difficulty, lock quality, wheel quality, slot spacing, and cable routing. These findings indicate that invention-oriented product development must evaluate both the main architectural novelty and the implementation details that influence adoption. The drawer-type architecture is therefore not only a different external form; it is a product-architecture response to a queueing bottleneck that must still satisfy capacity, security, stability, mobility, and maintenance requirements.

The findings are also consistent with adjacent research on mobile carts and workflow redesign. Gille [14] showed that cart geometry and wheel behavior can influence manual-handling forces and injury-prevention potential, supporting the view that cart design affects user effort. Hefter et al. [15] redesigned bedside supply carts through participatory human-factors methods and improved workflow access in a demanding environment. Although the present study addresses school device management rather than healthcare work, the underlying design principle is similar: mobile storage artifacts shape workflow because they structure access, visibility, motion, and sequence. Lamé et al. [16] argued that design expertise can function as a quality-improvement strategy. The present article provides an applied example in which design expertise improved an everyday infrastructure artifact by converting an observed workflow bottleneck into a measurable product-architecture intervention.

Figure 7 provides an additional interpretation of the validation results. The satisfaction scores were not simply a general endorsement of the prototype; they show that the solution preserved trust-related and adoption-related requirements while improving handling efficiency. Reliable locking/security received the highest score, which is important because schools manage expensive shared devices and require confidence in custody. Preference for drawer storage and effective storage with reduced queueing confirmed the intended access innovation. Easier plug alignment and reduced collisions supported the secondary requirements derived from opportunity scoring and competitor benchmarking. The lower but still positive score for reduced squatting or bending indicates a remaining ergonomic opportunity, especially for lower drawers, younger pupils, or users handling heavier devices.

The study has limitations. The field validation used aggregate session data, and the baseline and prototype sessions involved different numbers of users. The opportunity-scoring sample was modest, and the competitor benchmark relied on one online retail platform. The concept tests were not balanced randomized experiments, and individual-level repeated timing data were not collected. Therefore, the results should be interpreted as descriptive design-stage prototype-validation evidence rather than as a statistically generalizable effect estimate. Future research should include larger multi-school trials, participant-level timing records, balanced access-concept conditions, randomized or counterbalanced testing sequences, ergonomic posture measurements, long-term durability testing, electrical safety certification data, and maintenance logs.

These limitations also define the next stage of engineering development. A rigorous follow-up experiment should recruit substantially more participants from multiple schools, standardize device mass and size, record repeated participant-level trials, apply video-based motion and posture analysis, and analyze repeated measurements using analysis of variance or mixed-effects models when the data structure supports such analysis. For engineering qualification, the prototype should undergo drawer-load testing, rail stress analysis, anti-tip moment testing, dynamic movement stability testing, vibration testing, thermal monitoring during charging, and electrical safety certification. Future design iterations should also investigate USB-C fast charging, energy monitoring, modular cable trays, inventory status sensing, and sustainable materials.

5. Conclusions

This study designed and field-validated a drawer-type tablet/laptop charging cart for K-12 digital learning infrastructure. The main novelty lies in integrating a bilateral drawer-access product architecture with a field-informed engineering design and validation workflow. Unlike conventional front-opening charging cabinets that concentrate retrieval and return activities at a single access face, the proposed architecture creates two lateral access zones and converts serial device handling into parallel handling within one mobile cabinet.

The study translated a routine classroom bottleneck into a measurable product-architecture innovation by combining Lean Product and Process Development, jobs-to-be-done inquiry, outcome-driven opportunity scoring, contextual inquiry, competitor benchmarking, product essence mapping, A3 synthesis, comparative concept testing, and classroom field validation. This workflow linked observed school-device handling problems to product requirements, design variables, prototype construction, and validation indicators.

The principal empirical finding is that bilateral drawer access improved device-handling performance under the tested conditions. In comparative concept testing, the drawer-type concept achieved 4.4 s/device and was the only access concept that met the target of less than 5 s/device. In classroom field validation, the prototype reduced average handling time from 10.9 to 4.8 s/device and increased throughput from 5.5 to 12.5 devices/min. Post-use satisfaction was also positive, with all measured items scoring above 4.0 on a five-point scale.

These findings should be interpreted within the design-stage scope of the study. The timing data, opportunity scores, and satisfaction ratings support prototype feasibility, design refinement, and the promise of the drawer-type architecture. They do not constitute final proof of statistically generalizable superiority, certification-level mechanical safety, thermal performance, electrical safety, or long-term durability.

The practical implication is that procurement and design criteria for school charging carts should not be limited to capacity and electrical specifications. Handling time, access direction, queue dispersion, plug visibility, cable maintainability, anti-tip stability, custody, classroom fit, and user satisfaction should also be considered. The methodological implication is that Lean Product and Process Development combined with outcome-driven opportunity scoring can support applied engineering innovation by linking user outcomes to physical product architecture and field validation. Future work should extend the present design-stage evidence through larger multi-school trials, balanced repeated experiments, ergonomic assessment, mechanical and electrical safety verification, durability testing, and long-term maintenance evaluation.