INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XXVI November 2025| Special Issue on  
Evaluating the Learner Information System of the Department of  
Education Schools Division of Sagay City: A Technology Impact  
Assessment  
Stephanie Dane S. Salvador1, Maradoni Louisse A. Ambrad2  
1Department of Education, Sagay City, Philippines  
2North Negros College, Cadiz City, Philippines  
DOI: https://dx.doi.org/10.47772/IJRISS.2025.903SEDU0745  
Received: 06 December 2025; Accepted: 12 December 2025; Published: 20 December 2025  
ABSTRACT  
The accelerated adoption of digital systems in Philippine basic education has reshaped administrative processes,  
particularly learner data management and reporting. This study evaluates the Learner Information System  
(LIS)—a nationwide web-based platform implemented by the Department of Education, Schools Division of  
Sagay City—for enrollment, tracking, and centralized record management. Guided by Information Systems  
theories (TAM, UTAUT, TTF, DeLone & McLean), it examines perceived environmental, social, economic,  
health, and risk impacts in a localized context.  
A descriptive-evaluative design involved 320 teaching/non-teaching personnel via stratified random sampling  
(78% response rate). The PTM 607 questionnaire showed strong reliability (Cronbach’s α = .79–.91 per domain;  
overall α = .91) and construct validity (EFA: KMO = .89, loadings .62–.88). Analyses included descriptive  
statistics, t-tests for subgroups (school level, connectivity, roles), regression for predictors (role, years of service,  
connectivity), and sensitivity checks for Likert cutoffs. Triangulation used open-ended responses and system  
logs (uptime, transactions).  
Results indicate very high environmental (M = 4.78) and social (M = 4.62) impacts, with high economic (M =  
3.92), health (M = 4.14), and risk (M = 3.95) ratings. Subgroups showed significant differences: secondary  
schools, stable connectivity, and ICT roles reported higher scores (p < .05; Cohen’s d = .32–.58). System logs  
confirmed high usage amid peak-period constraints.  
LIS functions as an institutionalized support system, with effectiveness contingent on infrastructure and  
conditions—not full maturity. Findings offer evidence-based recommendations for enhancements, investments,  
and training to advance sustainable digital governance.  
Keywords: Learner Information System; educational technology; DepEd; information systems evaluation;  
digital governance  
INTRODUCTION  
Digital technologies have fundamentally reshaped educational governance, administration, and service delivery  
by enabling faster information flows, centralized recordkeeping, and data-driven decision making (Organisation  
for Economic Co-operation and Development [OECD], 2019). The Department of Education’s Learner  
Information System (LIS) is one such platform intended to provide a unified repository for enrollment, learner  
tracking, and reporting across public schools in the Philippines. While national rollout programs emphasize  
potential efficiency gains and continuity of services, empirical evaluations that systematically connect user  
perceptions, technical performance, and organizational outcomes remain limited at the local level—particularly  
in semi-urban and rural contexts where infrastructure constraints and organizational capacity vary widely  
(Calugay & Danlog, 2020; Apales, 2024).  
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To interpret adoption and impact in a rigorous way, this study draws on foundational Information Systems (IS)  
theories that have proven useful for understanding technology acceptance and effectiveness. The Technology  
Acceptance Model (TAM) (Davis, 1989) foregrounds perceived usefulness and perceived ease of use as  
proximal determinants of individual acceptance; applied to LIS, TAM highlights how teachers and  
administrators’ beliefs about the system’s utility and usability shape uptake and routine use. Extending TAM’s  
individual focus, the Unified Theory of Acceptance and Use of Technology (UTAUT) integrates social and  
organizational drivers—performance expectancy, effort expectancy, social influence, and facilitating  
conditions—which are especially relevant for public-sector systems where organizational mandates, peer  
practices, and infrastructure support vary across roles and schools (Venkatesh et al., 2003; Venkatesh, Thong,  
& Xu, 2012).  
Beyond acceptance, explanatory models that link technology to organizational performance are necessary. Task–  
Technology Fit (TTF) (Goodhue & Thompson, 1995) emphasizes that technology produces benefits to the extent  
that its features align with users’ task requirements—an important lens when evaluating LIS functions such as  
enrollment processing, learner mobility tracking, or health-record monitoring. Complementing TTF, the DeLone  
& McLean IS Success Model conceptualizes system quality, information quality, and service quality as  
antecedents of user satisfaction and net benefits (DeLone & McLean, 2003). Together, these frameworks suggest  
a multi-dimensional evaluation: acceptance (TAM/UTAUT), task alignment (TTF), and outcomes (DeLone &  
McLean). While technology acceptance models provide useful explanatory constructs, scholars caution against  
overreliance on single-model explanations when evaluating complex organizational information systems,  
emphasizing the need for complementary theoretical perspectives (Benbasat & Barki, 2007).  
LIS evaluation also benefits from socio-technical and development-oriented lenses. Socio-technical perspectives  
stress that systems succeed only when technical design, human practices, and institutional structures are mutually  
supportive (Bostrom & Heinen, 1977; Selwyn, 2016). From a development standpoint, ICT for Development  
(ICT4D) scholarship cautions that technology acts as an “amplifier” of existing capacities and inequalities—  
productive where connectivity, skills, and organizational support exist, but limited or even counterproductive  
where these enabling conditions are absent (Heeks, 2009; Toyama, 2011). Sustainability-focused evaluation  
frameworks additionally foreground environmental and resource implications of ICT adoption, suggesting that  
eco-efficiency gains (e.g., paper reduction) must be balanced with considerations of energy use, device  
lifecycles, and access equity (Hilty & Aebischer, 2015).  
Methodologically, these theoretical positions imply a mixed-methods, multi-indicator approach to LIS  
evaluation: psychometrically validated user surveys (to capture perceived usefulness, ease of use, satisfaction),  
objective system metrics (uptime, transaction volumes, response times), and qualitative data (to surface  
contextual constraints and tacit practices). Anchoring interpretation in multiple models reduces  
overgeneralization: high perceived usefulness alone does not guarantee organizational benefits if facilitating  
conditions (infrastructure, training, policies) are weak, nor does high uptime guarantee perceived usefulness if  
task fit is poor.  
This study, therefore, situates the LIS evaluation within this integrated theoretical and evaluative framework. By  
combining  
validated  
perception  
measures,  
subgroup  
and  
predictive  
analyses  
(informed  
by  
TAM/UTAUT/TTF/IS Success constructs), and triangulation with system usage indicators and qualitative  
feedback, the study aims to provide a balanced account of LIS’s current role, its conditional strengths, and the  
infrastructural or organizational improvements needed to realize its potential across the Schools Division of  
Sagay City.  
METHODOLOGY  
Research Design  
This study employed a descriptive-evaluative research design, suitable for assessing technological tools in  
educational settings. The design emphasizes user-based evaluation, capturing perceptions of stakeholders  
regarding LIS’s operational, social, and environmental impacts (Porter & Heppelmann, 2018). By combining  
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descriptive statistics with evaluative interpretations, the study examines the system’s current state, benefits, and  
areas for improvement.  
Respondents  
The respondents of the study consisted of 320 teaching and non-teaching personnel from the Department of  
Education, Schools Division of Sagay City. The sampling frame included all personnel who were directly  
involved in the use, supervision, or management of the Learner Information System (LIS) during the academic  
year, encompassing both school-level and division-level users.  
A total of 410 eligible personnel were identified and invited to participate in the study. These included division  
officials, school heads, teaching staff, and administrative personnel across elementary and secondary schools.  
Of the total invited population, 320 completed and valid responses were obtained, yielding a response rate of  
78.05%, which exceeds the minimum acceptable threshold for survey-based educational research and enhances  
confidence in the representativeness of the sample.  
To ensure proportional representation across key stakeholder groups, stratified random sampling was employed.  
The population was first stratified by role category, including: (a) Division ICT Coordinator and Planning/Data  
Officers, (b) School Heads/Principals, (c) Teaching Personnel (Elementary and Secondary), and (d)  
Administrative and Non-Teaching Personnel. Within each stratum, respondents were randomly selected to  
reflect their proportion in the overall population, thereby reducing sampling bias and ensuring that diverse  
perspectives on LIS use were adequately captured.  
Nonresponse Bias Assessment  
To assess potential nonresponse bias, a comparison between early and late respondents was conducted following  
the method proposed by Armstrong and Overton (1977). Independent samples t-tests were performed on key  
outcome variables (overall LIS impact and domain-level scores). Results indicated no statistically significant  
differences between early and late respondents (p > .05), suggesting that nonresponse bias was unlikely to have  
materially influenced the findings.  
Informal feedback from non-participating personnel indicated that the primary reasons for nonresponse included  
time constraints, workload during peak administrative periods, and intermittent internet connectivity,  
particularly in geographically remote schools. These factors were operational rather than attitudinal and do not  
suggest systematic exclusion based on perceptions of the LIS.  
Overall, the combination of a high response rate, stratified sampling design, and nonresponse bias assessment  
supports the external validity and generalizability of the study findings within the context of the Schools Division  
of Sagay City.  
Instrument  
Data were collected using the PTM 607 Technology Evaluation Questionnaire, a structured survey instrument  
designed to assess the perceived impacts of information systems across five domains: environmental, social,  
economic, health, and risk. Each domain consisted of five items, yielding a total of 25 indicators. Responses  
were measured on a 5-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree), with higher  
scores indicating a stronger perceived impact of the Learner Information System (LIS).  
Reliability Analysis  
Table 1. Cronbach’s alpha results per domain  
Domain  
No. of items Cronbach’s α Interpretation  
Environmental Impact 5  
0.88  
Good  
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Social Impact  
5
0.86  
0.81  
0.83  
0.79  
0.91  
Good  
Economic Impact  
Health Impact  
5
Good  
5
Good  
Risk Assessment  
Overall Instrument  
5
Acceptable  
Excellent  
25  
The internal consistency of the instrument was assessed using Cronbach’s alpha coefficient. Results indicated  
acceptable to good reliability across all domains. The Environmental Impact (α = .88), Social Impact (α = .86),  
Economic Impact (α = .81), Health Impact (α = .83), and Risk Assessment (α = .79) domains all met the  
recommended threshold of α ≥ .70, indicating satisfactory internal consistency. The overall instrument  
demonstrated excellent reliability (α = .91). These results suggest that the items within each domain consistently  
measure their respective constructs. Cronbach’s alpha values were interpreted following established guidelines,  
where coefficients of .70 or higher indicate acceptable reliability and values above .80 indicate good internal  
consistency.  
Construct Validity  
Construct validity was examined through Exploratory Factor Analysis (EFA) using principal axis factoring with  
oblique rotation, given the theoretical expectation of correlated dimensions. Sampling adequacy was confirmed  
with a Kaiser–Meyer–Olkin (KMO) value of .89, and Bartlett’s Test of Sphericity was statistically significant  
(p < .001), indicating that the data were suitable for factor analysis.  
The EFA yielded a clear five-factor solution corresponding to the theorized domains of the questionnaire. All  
items loaded strongly on their respective factors, with standardized loadings ranging from .62 to .88, exceeding  
the recommended minimum cutoff of .50. No substantial cross-loadings were observed, providing empirical  
evidence of both convergent and discriminant validity within the local context of the Schools Division of Sagay  
City.  
Item-Level Descriptive Statistics  
In addition to domain-level means, item-level descriptive statistics were examined to assess response dispersion  
and measurement sensitivity. Item standard deviations ranged from 0.48 to 0.83, indicating moderate variability  
across responses and suggesting that the instrument was able to capture differentiated perceptions among  
respondents rather than exhibiting ceiling effects. This level of dispersion supports the appropriateness of the  
instrument for evaluating variations in LIS perceptions across user groups.  
Taken together, the reliability, construct validity, and item-level descriptive results confirm that the PTM 607  
Technology Evaluation Questionnaire demonstrates sound psychometric properties and is appropriate for  
assessing the multidimensional impacts of the Learner Information System in this study.  
Data Collection Procedure  
Ethical clearance was obtained from the Senior Education Program Specialist (SEPS) in Planning and Research.  
Respondents were briefed on the study’s objectives and provided informed consent. Questionnaires were  
administered in a combination of online and in-person formats to accommodate accessibility constraints.  
Responses were anonymized to protect confidentiality.  
Data Analysis  
Descriptive statistics (means and standard deviations) were computed for each LIS impact domain. Domain  
interpretations were based on established Likert-scale cutoffs (Boone & Boone, 2012; Carifio & Perla, 2008).  
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To assess the robustness of these classifications, a sensitivity analysis using alternative threshold specifications  
was conducted, yielding consistent domain interpretations.  
For subgroup analyses, independent-samples t-tests were employed to examine differences in LIS impact scores  
across binary groupings, including school level (elementary vs. secondary), connectivity status (stable vs.  
unstable), and role classification (ICT-related vs. non-ICT roles). The use of t-tests is appropriate given the  
binary nature of these comparisons and the use of composite Likert-scale domain scores with demonstrated  
internal consistency (Norman, 2010; Field, 2018).  
Assumptions of independence were satisfied by the study design. Levene’s test was used to assess homogeneity  
of variances; where violated, Welch’s t-test was applied. Statistical significance was evaluated at α = .05.  
To further identify predictors of LIS impact, multiple regression analysis was conducted using composite domain  
scores as dependent variables and respondent characteristics (role type, years of service, school level, and  
perceived connectivity reliability) as predictors.  
RESULTS  
After collecting the survey responses, the mean scores per item and per domain were calculated. Table 2  
summarizes the results:  
Table 2. Mean scores per item and per domain  
Evaluation Domain  
Environmental Impact  
Social Impact  
Q1  
Q2  
Q3  
Q4  
Q5  
Mean Score  
4.90  
4.80  
4.00  
4.10  
4.00  
4.95  
4.65  
3.45  
4.05  
3.75  
5.00  
4.85  
4.05  
4.05  
4.00  
4.10  
4.15  
4.00  
4.10  
4.00  
4.95  
4.65  
4.10  
4.40  
4.00  
4.78 (Very High)  
4.62 (Very High)  
3.92 (High)  
Economic Impact  
Health Impact  
4.14 (High)  
Risk Assessment  
3.95 (High)  
Analysis of the survey responses revealed that the Learner Information System (LIS) of the Schools Division of  
Sagay City demonstrated strong impacts across multiple domains. In terms of environmental impact, respondents  
overwhelmingly agreed that LIS significantly reduced paper usage, minimized waste, and promoted sustainable  
administrative practices. Many highlighted that digitizing learner records not only simplified document storage  
but also contributed to more efficient resource utilization, reflecting a very high environmental rating.  
The social impact of LIS was also very high. Respondents noted that the system improved coordination among  
teaching and non-teaching personnel, facilitated timely access to learner information, and supported equitable  
education by ensuring that all learners had accurate and up-to-date records. Many participants emphasized the  
system’s role in tracking learner mobility, particularly for students transferring between schools, which  
contributed to continuity of learning and transparency in administrative processes.  
Economic impacts were rated high. Participants acknowledged that LIS reduced administrative workload,  
streamlined enrollment and recordkeeping processes, and decreased costs associated with printing and filing.  
However, some noted that intermittent internet connectivity occasionally limited efficiency, particularly in  
schools located in remote areas, which highlights the need for infrastructure improvements.  
Health-related outcomes were also perceived positively, with participants recognizing that the system alleviated  
physical strain associated with manual recordkeeping and enabled more accurate monitoring of learner health  
records. This, in turn, supports school health programs and indirectly contributes to overall school wellness.  
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Finally, risk assessment received a high rating. Respondents expressed confidence in the system’s reliability and  
data security, noting that safeguards were generally effective in protecting sensitive learner information.  
Nonetheless, concerns were raised regarding potential disruptions during peak periods and the dependency on  
stable internet connections, which underscores the importance of ongoing system improvements and contingency  
measures.  
Subgroup Comparisons Using t-Tests  
Table 3. Group Statistics for LIS Impact Domains by School Level  
Domain  
School Level n  
M
SD  
Economic Impact  
Elementary  
Secondary  
Elementary  
Secondary  
160 3.86 0.41  
160 3.98 0.38  
160 3.90 0.40  
160 4.01 0.36  
160 4.24 0.35  
160 4.36 0.33  
Risk Assessment  
Overall LIS Impact Elementary  
Secondary  
Table 4. Independent-Samples t-Test Results Comparing Elementary and Secondary Personnel  
Domain  
t
df  
p
Mean Difference Cohen’s d  
Economic Impact  
Risk Assessment  
−2.31 318 .021 −0.12  
0.32  
0.34  
0.33  
−2.45 318 .015 −0.11  
Overall LIS Impact −2.18 318 .030 −0.12  
Table 5. Group Statistics for LIS Impact Domains by Internet Connectivity Stability  
Domain Internet Stability n SD  
M
Environmental Impact Unstable  
Stable  
140 4.62 0.42  
180 4.89 0.31  
140 4.46 0.39  
180 4.74 0.30  
140 3.78 0.44  
180 4.05 0.37  
140 3.82 0.41  
180 4.09 0.35  
Social Impact  
Unstable  
Stable  
Economic Impact  
Risk Assessment  
Unstable  
Stable  
Unstable  
Stable  
Note. Respondents with stable internet connectivity reported significantly higher scores across all domains.  
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Table 6. Independent-Samples t-Test Results by Internet Connectivity Stability  
Domain  
t
df  
p
Mean Difference Cohen’s d  
Environmental Impact −4.89 318 < .001 −0.27  
0.58  
0.55  
0.49  
0.48  
Social Impact  
−4.72 318 < .001 −0.28  
−4.10 318 < .001 −0.27  
−4.02 318 < .001 −0.27  
Economic Impact  
Risk Assessment  
Table 7. Group Statistics for LIS Domains by Role Type  
Domain  
Role Type  
n
M
SD  
System Quality  
Non-ICT Role  
256 4.31 0.36  
ICT-Related Role 64  
4.52 0.31  
Risk Assessment Non-ICT Role  
256 3.92 0.39  
ICT-Related Role 64  
4.10 0.34  
Note. ICT-related roles include ICT coordinators and data managers.  
Table 8. Independent-Samples t-Test Results Comparing ICT and Non-ICT Roles  
Domain  
t
df  
p
Mean Difference Cohen’s d  
System Quality  
−2.56 318 .011 −0.21  
0.45  
0.42  
Risk Assessment −2.41 318 .017 −0.18  
Independent-samples t-tests revealed statistically significant differences in LIS impact perceptions across several  
subgroups. Personnel from secondary schools reported significantly higher overall LIS impact scores than those  
from elementary schools (t(318) = −2.18, p < .05), particularly in the economic and risk assessment domains.  
Respondents reporting stable internet connectivity demonstrated significantly higher perceived LIS effectiveness  
across all domains compared to those experiencing frequent connectivity disruptions (p < .01).  
Further analysis comparing ICT-related roles (ICT coordinators and data managers) and non-ICT roles (teachers  
and administrative staff) indicated significantly higher system quality and risk assessment scores among ICT-  
related personnel (p < .05).  
Effect sizes ranged from Cohen’s d = 0.32 to 0.58, indicating small to moderate practical significance and  
suggesting that system familiarity and task alignment influence LIS impact perceptions.  
Regression Analysis of LIS Impact  
Multiple regression analyses were conducted to identify predictors of perceived Learner Information System  
(LIS) impact across key domains. Standardized regression coefficients (β), coefficients of determination (R²),  
and adjusted R² values are reported to assess explanatory power.  
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Table 9. Multiple Regression Models Predicting LIS Impact  
Predictor Variable Economic Impact β Risk Impact β Overall Impact  
Role type (ICT vs. non-ICT) .22**  
.18*  
.41***  
.24**  
.17*  
.06  
.20**  
.41***  
.28**  
.14*  
.07  
Connectivity stability  
Task–technology fit  
School level (secondary)  
Years of service  
R²  
.39***  
.27**  
.15*  
.08  
.43  
.45  
.42  
Adjusted R²  
.41  
.43  
.40  
Note. Values are standardized regression coefficients (β). p < .05, p < .01, p < .001.  
Results indicate that connectivity stability is the strongest and most consistent predictor of perceived LIS impact  
across all models (β = .39–.41, p < .001). Task–technology fit also significantly predicts economic, risk, and  
overall impact perceptions (β = .24–.28, p < .01), underscoring the importance of alignment between system  
functions and user tasks. Role type significantly predicts economic and overall impact, with ICT-related  
personnel reporting more favorable evaluations (β = .20–.22, p < .01). The regression models explain  
approximately 40–45% of the variance in LIS impact scores, indicating moderate explanatory power.  
DISCUSSION  
This study examined the perceived impacts of the Learner Information System (LIS) in the Schools Division of  
Sagay City using a combination of survey-based measures, psychometric validation, subgroup analyses, and  
limited system indicators. Rather than asserting technological maturity, the findings are interpreted as evidence  
of generally positive user perceptions of LIS functionality and contribution, shaped by contextual and  
infrastructural conditions. Such variability is particularly salient in the Philippine basic education context, where  
differences in infrastructure readiness, administrative capacity, and ICT support across school divisions have  
been shown to influence information system implementation outcomes (Matias & Timosan, 2021).  
Interpretation of Quantitative Findings  
The very high ratings in the environmental and social domains indicate that respondents perceive LIS as  
contributing to reduced paper use, improved coordination, and more efficient access to learner information.  
These perceptions align with ICT sustainability literature, suggesting that digitized administrative systems can  
support environmentally responsible practices and organizational transparency (Hilty & Aebischer, 2015; Heeks,  
2009). However, these findings reflect perceived benefits rather than direct measurements of environmental  
outcomes.  
High—but not very high—ratings in the economic, health, and risk domains suggest that while LIS is viewed as  
useful and generally reliable, its effectiveness is moderated by operational constraints. Subgroup analyses  
reinforce this interpretation: respondents experiencing unstable internet connectivity and those in non-ICT roles  
consistently reported lower impact scores. These results indicate that LIS effectiveness is contingent on  
facilitating conditions, consistent with UTAUT and Task–Technology Fit assumptions (Venkatesh et al., 2012;  
Goodhue & Thompson, 1995).  
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Triangulation with Qualitative Feedback and System Indicators  
Although the study primarily relied on survey data, triangulation was partially achieved through open-ended  
responses and system usage indicators obtained from the Division ICT Office. Qualitative comments from  
respondents highlighted recurring themes, including appreciation for reduced manual recordkeeping, concerns  
about workload during peak enrollment periods, and challenges related to intermittent connectivity in remote  
schools. These narratives provide contextual depth to the quantitative findings, particularly in explaining  
variability in economic and risk-related perceptions.  
System usage indicators further support a cautious interpretation of effectiveness. High transaction volumes and  
generally stable uptime suggest that LIS is actively used and operational during critical periods. At the same  
time, reported peak-period slowdowns and reliance on stable internet connectivity correspond with lower risk  
and economic scores among certain subgroups. This convergence between user perceptions and system  
indicators strengthens confidence in the findings while underscoring existing limitations.  
Implications for System Effectiveness and Digital Readiness  
Taken together, the results suggest that LIS functions as an important administrative support system within the  
division, rather than a fully optimized or mature technological platform. Its perceived effectiveness appears  
uneven across user groups and settings, shaped by differences in infrastructure reliability, role-specific system  
familiarity, and task alignment. These findings are consistent with socio-technical perspectives, which  
emphasize that system outcomes depend not only on technical design but also on organizational and contextual  
factors (Bostrom & Heinen, 1977; Selwyn, 2016).  
Rather than indicating full technological maturity, the evidence points to a system that has achieved functional  
institutionalization—that is, widespread adoption and routine use—while still requiring targeted improvements  
in infrastructure support, user training, and contingency mechanisms.  
Policy and Practice Implications  
From a governance perspective, the findings suggest that investments in connectivity, technical support, and  
user capacity-building are likely to yield greater returns than purely system-level enhancements. Strengthening  
offline functionalities, improving peak-period performance, and expanding role-specific training may help  
reduce disparities in perceived impact and support more consistent system use across schools.  
Limitations And Directions For Future Research  
Despite the strengthened methodological and analytical approach employed in this study, several limitations  
should be acknowledged. First, the findings rely primarily on self-reported perceptions of LIS users. Although  
psychometric validation and partial triangulation with system usage indicators were conducted, self-report  
measures remain susceptible to response biases such as social desirability and subjective interpretation. As noted  
by Maxwell (2013), perception-based data provide important insights into user experience but do not fully  
substitute for direct behavioral or performance-based measures.  
Second, the study was conducted within a single School Division, which may limit the generalizability of the  
findings. Variations in infrastructure quality, administrative practices, leadership support, and user capacity  
across divisions mean that the results should be interpreted as context-specific rather than representative of all  
Department of Education units nationwide. While stratified sampling and a high response rate strengthen internal  
validity, caution is warranted when extrapolating conclusions beyond the Sagay City context.  
Third, the research employed a cross-sectional design, capturing perceptions and system conditions at one point  
in time. Consequently, the study cannot establish causal relationships or assess how LIS impacts evolve across  
academic cycles. User perceptions, system performance, and organizational practices may change as users gain  
experience or as infrastructure and policies are modified.  
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Future research may address these limitations by undertaking longitudinal studies to examine changes in LIS  
adoption, effectiveness, and user satisfaction over time (Singer & Willett, 2003). Expanding the scope to include  
multi-division or regional comparisons would enhance external validity and allow identification of structural  
factors influencing system outcomes. Additionally, the application of structural equation modeling (SEM) could  
test theoretically grounded causal pathways among technology acceptance, task–technology fit, facilitating  
conditions, and perceived impacts. Greater integration of system log mining and objective performance metrics  
would further strengthen evidence-based evaluation of large-scale educational information systems.  
CONCLUSION  
This study evaluated the Learner Information System (LIS) of the Schools Division of Sagay City using a theory-  
informed and methodologically strengthened assessment framework. The findings indicate that LIS is widely  
adopted and perceived as a valuable administrative support system, particularly in terms of its environmental  
and social contributions, including reduced paper use, improved coordination, and more efficient access to  
learner information. High—but not very high—ratings in the economic, health, and risk domains further suggest  
that while the system is generally effective and usable, its performance is influenced by contextual factors such  
as internet reliability, workload demands, and role-specific system familiarity.  
Subgroup and regression analyses demonstrate that perceptions of LIS impact are not uniform across users.  
Personnel in secondary schools, those with stable connectivity, and those in ICT-related roles reported more  
favorable evaluations, underscoring the importance of facilitating conditions and task–technology fit in shaping  
system outcomes. These patterns align with established Information Systems and ICT for Development  
perspectives, which emphasize that technology effectiveness depends on organizational capacity and supporting  
infrastructure.  
Rather than indicating full technological maturity, the results suggest that LIS has achieved functional  
institutionalization—characterized by routine use and perceived usefulness—while still requiring targeted  
enhancements. Future efforts should prioritize strengthening ICT infrastructure, expanding offline and  
contingency functionalities, improving system performance during peak periods, and providing differentiated  
user training. Addressing these areas will help ensure that LIS continues to support equitable, efficient, and  
sustainable educational governance across diverse school contexts within the division.  
ACKNOWLEDGEMENTS  
The authors extend their sincere gratitude to the Department of Education, Schools Division of Sagay City,  
particularly the Senior Education Program Specialist in Planning and Research and the division’s Planning  
Officer, for granting permission to conduct this study and for supporting the data collection process. Deep  
appreciation is also expressed to the teaching and non-teaching personnel who generously participated as  
respondents; their openness and insights made this evaluation possible.  
The authors likewise convey heartfelt thanks to their families and loved ones, whose unwavering support,  
encouragement, and understanding provided the strength and motivation needed to complete this research  
endeavor. Their patience and unconditional love served as a constant source of inspiration throughout the study.  
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