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COLLEGE FILL RATE

87.9%

WoW +2.1%

Enrolled ÷ Capacity

FACULTY COVERAGE

93.5%

WoW +1.4%

Assigned ÷ Required load

ROOM UTILIZATION

71.0%

WoW +4.4%

Occupied hrs ÷ Available hrs

GRADES COMPLIANCE

82.0%

WoW +5.1%

Submitted ÷ Expected sections

TODAY

Classes & Room Status

Live

Classes Today

118

3 cancelled / rescheduled

Rooms Available Now

Labs included

Conflicts Today

Room / faculty overlaps

Time	Section	Course	Room	Faculty	Status
7:30–9:00	BSIT-3A	IPT2 (Lab)	B1.26	Dela Cruz	On-going
9:00–10:30	BSCS-2B	DSA	B2.11	Rivera	Starts 9:00
10:30–12:00	BSEd-1C	SOFAPP	Lab 3	Chiong	Ready
1:00–2:30	BSBA-4A	Strategic Mgmt	B3.07	Santos	Substitute Needed
3:00–4:30	BSIT-1D	Prog 1	B1.22	Garcia	Cancelled

COMPLIANCE QUEUE

INC & Grade Change

Open INC Cases

INC Near Deadline

Grade Change Requests

Prioritize cases ≤3 days to deadline.

TOP MOVERS

Sections with Biggest WoW Fill Change

Section	Program	Change	Now	Last Week
BSIT-1A	BSIT	+8.2%	96.0%	88.7%
BSCS-2C	BSCS	+6.4%	92.1%	86.5%
BSEd-3B	BSEd	+5.1%	89.9%	85.6%
BSBA-4D	BSBA	+4.7%	90.3%	86.2%

EXCEPTIONS

Items Needing Attention

Critical: 3 Advisory: 0

Critical

Type	Detail	Owner	SLA
Fill Rate Low	College fill 87.6% below 88%	Acad Coord	48h
Conflicts Spike	6.96 conflicts/1k students	Scheduling	24h
Grades Overdue	Submission 82.0% below 85%	Depts/Chairs	72h

Advisory

Type	Detail	Owner	SLA
No advisory exceptions.

KPI SUMMARY

College Performance Dashboard

Comprehensive view of all key performance indicators with historical trends and targets.

COLLEGE PERFORMANCE

KPI Achievement vs Targets

Fill Rate 87.9%

Target: 85% +2.9%

Faculty Coverage 93.5%

Target: 90% +3.5%

Room Utilization 71.0%

Target: 75% -4.0%

Grades Compliance 82.0%

Target: 90% -8.0%

PERFORMANCE TRENDS

KPI Progress Over Time

100 95 90 85 80 75 70 65 60 55 50

W1 W2 W3 W4 W5 W6 W7 W8

Fill Rate

Faculty Coverage

Room Utilization

Grades Compliance

DEPARTMENT PERFORMANCE

KPI Breakdown by Academic Department

Department	Fill Rate	Faculty Coverage	Room Utilization	Grades Compliance	Overall Score
Information Technology	92.1%	95.3%	78.2%	88.5%	88.5%
Computer Science	89.7%	91.2%	72.4%	85.2%	84.6%
Business Administration	85.3%	88.9%	68.7%	79.8%	80.7%
Education	82.6%	84.5%	65.3%	76.4%	77.2%

Skolaris SIS · College Academic Console · Nov 26, 2025, 4:46 PM

ALERTS & EXCEPTIONS

College Alert Management Center

Monitor, acknowledge, and resolve college-wide alerts and exceptions.

ACTIVE ALERTS

Critical & Advisory Items

Faculty Coverage Critical

IT Department has 5 vacant faculty positions affecting 5 sections

Faculty Sections Created: 2 hours ago

Room Overutilization

Building A rooms at 92% capacity during peak hours

Rooms Capacity Created: 5 hours ago

Grades Submission Delay

15 sections have not submitted grades (past deadline)

Grades Deadline Created: 1 day ago

ALERT STATISTICS

College Alert Overview

Critical Alerts

+2 since yesterday

Advisory Alerts

-3 since yesterday

Avg. Resolution Time

2.3d

SLA: 3.0 days

Acknowledgment Rate

78%

Target: 90%

ALERT CATEGORIES

Total Alerts

Faculty

25%

Rooms

20%

Grades

15%

Attendance

10%

Scheduling

Skolaris SIS · College Academic Console · Nov 26, 2025, 4:46 PM

ACADEMIC ANALYTICS

Enrollment Insights (College)

Comprehensive enrollment analysis, trends, projections, and demographic insights for campus planning and decision-making.

TOTAL ENROLLMENT

3,590

+230 from last week

Current active students

FILL RATE

87.9%

+1.8% WoW

Enrolled ÷ Capacity (4,100)

NEW ENROLLMENTS

142

-12 from last week

This week's new students

NEW

WITHDRAWAL RATE

2.3%

+0.4% WoW

Term-to-date withdrawals

ENROLLMENT TRENDS

Weekly College Intake

Actual Enrollment

Projected Enrollment

Previous Term

PROGRAM DISTRIBUTION

Enrollment by Academic Program

Information Technology

Computer Science

Business Administration

Education

Arts & Sciences

DEMOGRAPHIC INSIGHTS

Gender Distribution

Male

1,890

Male

Female

Other/Prefer not to say

YEAR LEVEL ANALYSIS

Distribution by Academic Year

920

First Year

850

Second Year

720

Third Year

680

Fourth Year

350

Graduate

Retention rate: 87.2% (Y1→Y2); 91.5% (Y2→Y3); 94.1% (Y3→Y4)

LEARNING MODALITY

Enrollment by Delivery Mode

Face-to-Face

Hybrid

Online

Average Age

21.4 years

Median Age

20.7 years

Hybrid modality shows 23% growth vs previous term

ENROLLMENT PROJECTIONS

Actual vs Projected Enrollment

Actual

Projected

Current Variance

+3.2%

Projected Final

3,820

Target

3,750

Confidence

High

DETAILED ENROLLMENT DATA

Section-Level Enrollment Analysis

Section Code	Program	Course	Faculty	Capacity	Enrolled	Fill Rate	Waitlist	Status
BSIT-3A	BSIT	Advanced Programming	Dela Cruz	40	38	95%	3	Optimal
BSCS-2B	BSCS	Data Structures	Rivera	35	32	91%	5	Optimal
BSBA-4A	BSBA	Strategic Management	Santos	45	36	80%	0	Healthy
BSEd-1C	BSEd	Foundations of Education	Chiong	30	22	73%	0	Underfilled
BSIT-1B	BSIT	Programming 1	Garcia	40	29	73%	0	Underfilled
BSCS-3C	BSCS	Algorithms	Ramos	35	35	100%	8	Overfilled
BSBA-2D	BSBA	Marketing Principles	Lopez	45	42	93%	2	Optimal
BSEd-4A	BSEd	Teaching Methods	Tan	30	28	93%	0	Healthy
BSIT-2C	BSIT	Web Development	Chen	40	35	88%	4	Optimal
BSCS-1A	BSCS	Intro to CS	Wang	35	25	71%	0	Underfilled
BSBA-3B	BSBA	Financial Accounting	Lim	45	40	89%	1	Optimal
BSEd-2B	BSEd	Child Development	Ong	30	24	80%	0	Underfilled
BSIT-4A	BSIT	Capstone Project	Dela Cruz	40	38	95%	0	Optimal
BSCS-4B	BSCS	AI Fundamentals	Rivera	35	34	97%	6	Overfilled
BSBA-1A	BSBA	Business Math	Santos	45	31	69%	0	Healthy

Showing 1-15 of 192 sections

ENROLLMENT INSIGHTS

Key Findings & Trends

Strong IT Program Growth

BSIT program shows 15% enrollment increase vs last term

Evening Class Demand

Evening sections filling 23% faster than daytime sections

First-Year Retention Concern

12.8% first-year attrition rate requires intervention

Hybrid Modality Success

Hybrid courses achieving 94% fill rate vs 78% for traditional

STRATEGIC RECOMMENDATIONS

Actionable Insights

Expand IT Program Capacity

Add 2 additional sections for high-demand courses

Evening Program Marketing

Allocate additional marketing budget to evening programs

First-Year Support Program

Develop targeted retention program for first-year students

ACADEMIC ANALYTICS

Section Health Trends & Monitoring

Comprehensive analysis of section performance, enrollment health, and at-risk indicators across all programs.

SECTION HEALTH SCORE

84.2%

+2.1% from last week

Overall college section health

A-

AT-RISK SECTIONS

-3 from last week

Requiring intervention

⚠

CRITICAL SECTIONS

+1 from last week

Immediate action needed

⚠

OPTIMAL SECTIONS

142

+8 from last week

Meeting all benchmarks

✓

FILTERS & CONTROLS

HEALTH DISTRIBUTION

Section Health Across Programs

Optimal

Healthy

At-Risk

Critical

BSIT

BSCS

BSBA

BSEd

BSA

BSP

HEALTH TRENDS

Section Health Over Time

Overall Health

At-Risk Sections

Critical Sections

RISK FACTORS ANALYSIS

Primary Contributors to Section Risk

Low Enrollment 42%

Poor Attendance 28%

Faculty Issues 15%

Academic Performance 10%

Other Factors 5%

SECTION HEALTH DETAILS

Comprehensive Section Health Monitoring

Section	Program	Enrollment Health	Attendance Rate	Grade Performance	Faculty Rating	Overall Health	Status
BSIT-3A	BSIT	95%	92%	88%	90%	91%	Optimal
BSCS-2B	BSCS	92%	89%	85%	88%	88%	Optimal
BSBA-4A	BSBA	80%	78%	82%	85%	81%	Healthy
BSEd-1C	BSEd	73%	85%	78%	80%	78%	Healthy
BSIT-1B	BSIT	65%	72%	68%	75%	69%	At-Risk
BSCS-3C	BSCS	58%	65%	62%	70%	63%	At-Risk
BSBA-2D	BSBA	45%	60%	55%	65%	55%	Critical
BSEd-4A	BSEd	82%	88%	85%	90%	86%	Optimal
BSIT-2C	BSIT	88%	85%	80%	82%	84%	Optimal
BSCS-1A	BSCS	70%	75%	72%	78%	73%	Healthy

Showing 1-10 of 165 sections

INTERVENTION RECOMMENDATIONS

Automated Action Items

Merge Under-enrolled Sections

Combine BSIT-1B and BSIT-1C (both below 65% capacity)

Faculty Support Needed

BSCS-2A showing declining student performance

Attendance Intervention

BSEd-3C attendance below 75% for 3 consecutive weeks

HEALTH METRICS EXPLANATION

How Section Health is Calculated

Optimal (80-100%): All metrics meeting or exceeding targets

Healthy (65-79%): Minor issues detected, monitoring recommended

At-Risk (50-64%): Significant issues requiring intervention

Critical (Below 50%): Immediate action required

Health Score Formula

Overall Health = (Enrollment Score × 0.3) + (Attendance Score × 0.25) + (Grade Performance × 0.25) + (Faculty Rating × 0.2)

ACADEMIC ANALYTICS

Faculty Load Insights

Comprehensive analysis of faculty workload distribution, utilization rates, and teaching capacity optimization.

FACULTY UTILIZATION

93.5%

+1.3% from last week

Assigned ÷ Required load

👥

VACANT LOAD

142

-18 units WoW

Remaining units to assign

📋

OVERLOADED FACULTY

+2 from last week

Exceeding capacity limits

⚠

AVG LOAD/FACULTY

16.8

+0.4 units WoW

Units per faculty member

👨‍🏫

LOAD DISTRIBUTION

Workload by Department

Assigned Load

Capacity

Information Technology

Computer Science

Business Administration

Education

General Education

IT Dept has highest utilization at 96.2%

Education Dept needs 45 more units

LOAD TRENDS

Weekly Faculty Utilization

Faculty Utilization

Vacant Load

Overload

LOAD STATUS

Faculty Distribution by Load Level

Underloaded (<15)

Optimal (15-18)

Heavy (19-23)

Overloaded (24+)

Optimal Range

15-18 units

Overload Limit

24 units

EMPLOYMENT TYPE

Load Distribution by Faculty Type

Full-time

Part-time

Adjunct

Full-time faculty carry 78% of total teaching load

COURSE LEVEL LOAD

Teaching Load by Course Level

Teaching Load

Faculty Count

Undergraduate

Graduate

Doctoral

Graduate courses: 28% of load, 15% of faculty

CAPACITY ANALYSIS

Departmental Capacity vs Utilization

Utilization %

Vacant Units

Overload Units

Total Capacity

2,880 units

Assigned Load

2,698 units

Vacant Load

182 units

Overload

86 units

FACULTY LOAD DETAILS

Individual Faculty Load Analysis

Faculty Name	Department	Rank	Employment	Required Load	Assigned Load	Utilization	Sections	Status
Dela Cruz, Maria	IT	Professor	Full-time	18 units	18 units	100%	4	Optimal
Rivera, Juan	CS	Associate Prof	Full-time	18 units	15 units	83%	3	Underloaded
Santos, Roberto	BA	Professor	Full-time	15 units	21 units	140%	5	Overloaded
Garcia, Lorna	IT	Assistant Prof	Full-time	18 units	12 units	67%	2	Underloaded
Chiong, Michael	Education	Instructor	Full-time	18 units	16 units	89%	3	Optimal
Ramos, Anna	CS	Assistant Prof	Full-time	18 units	20 units	111%	4	Overloaded
Tan, William	GenEd	Instructor	Part-time	12 units	12 units	100%	3	Optimal
Lim, Susan	BA	Associate Prof	Full-time	18 units	18 units	100%	4	Optimal
Ong, David	IT	Professor	Full-time	15 units	22 units	147%	5	Overloaded
Chen, Melissa	CS	Instructor	Adjunct	9 units	9 units	100%	2	Optimal
Wang, James	Education	Assistant Prof	Full-time	18 units	14 units	78%	2	Underloaded
Lopez, Patricia	GenEd	Instructor	Part-time	12 units	8 units	67%	2	Underloaded
Torres, Carlos	BA	Professor	Full-time	15 units	15 units	100%	3	Optimal
Flores, Angela	IT	Associate Prof	Full-time	18 units	18 units	100%	4	Optimal
Reyes, Mark	CS	Assistant Prof	Full-time	18 units	16 units	89%	3	Optimal

Showing 1-15 of 142 faculty members

FACULTY LOAD INSIGHTS

Key Findings & Trends

IT Department Optimization

96.2% utilization with balanced load distribution

Education Department Gap

45 units vacant, primarily in specialized courses

Overload Concentration

8 faculty members carrying 86 overload units

Adjunct Utilization

Adjunct faculty handling 22% of undergraduate courses

Graduate Course Distribution

15% of faculty teaching 28% of graduate load

LOAD OPTIMIZATION RECOMMENDATIONS

Actionable Insights

Redistribute Overload

Shift 42 units from overloaded to underloaded faculty

Hire Adjunct Faculty

Recruit 3 adjunct faculty for Education Department

Cross-Department Assignment

Assign IT faculty to general education courses

Load Balancing Algorithm

Run automated load optimization for next term

WORKLOAD PROJECTIONS

Next Term Faculty Capacity Planning

Projected Enrollment Increase

+8.2%

Requires +236 teaching units

Faculty Attrition

-3

Retirements and resignations

Required New Hires

2 full-time, 3 adjunct

Projected Utilization

91.8%

With current faculty pool

Capacity Planning Notes

IT Department at maximum capacity - consider adjunct hiring
Education Department can absorb additional load
Cross-training needed for specialized course coverage
Summer session can help balance annual load distribution

ACADEMIC ANALYTICS

Room Utilization Analytics

Comprehensive analysis of classroom and laboratory utilization, space optimization, and facility planning insights.

OVERALL UTILIZATION

71.0%

+3.0% from last week

Occupied hrs ÷ Available hrs

📊

PEAK UTILIZATION

89.2%

Tue 10:00-12:00

Highest utilization period

📈

AVAILABLE ROOMS

+2 from last week

Currently unoccupied rooms

🔍

UNDERUTILIZED ROOMS

-3 from last week

Below 40% utilization

📉

UTILIZATION TRENDS

Weekly Room Utilization Rate

Overall Utilization

Lecture Halls

Computer Labs

DAILY PATTERNS

Utilization by Day of Week

Mon

Tue

Wed

Thu

Fri

Sat

BUILDING ANALYSIS

Utilization by Building

Main Building

Science Bldg

Tech Center

Annex

Lab Wing

Most Utilized

Tech Center: 82%

Least Utilized

Annex: 58%

ROOM TYPE ANALYSIS

Utilization by Room Type

Lecture Hall

Classroom

Computer Lab

Science Lab

Specialized Lab

Computer labs at 94% utilization during peak hours

CAPACITY ANALYSIS

Room Usage vs Capacity

Underutilized (<40%)

Balanced (40-80%)

Highly Utilized (80-95%)

Overutilized (>95%)

68% of rooms used at optimal capacity (60-90%)

HOURLY UTILIZATION

Weekly Room Utilization Heatmap

Time	Mon	Tue	Wed	Thu	Fri	Sat
7:00-8:00	45%	52%	48%	50%	38%	12%
8:00-9:00	65%	72%	68%	70%	55%	18%
9:00-10:00	78%	85%	80%	82%	62%	25%
10:00-11:00	82%	89%	84%	86%	68%	32%
11:00-12:00	85%	89%	87%	88%	72%	38%
12:00-13:00	68%	75%	72%	74%	58%	28%
13:00-14:00	72%	78%	75%	77%	62%	35%
14:00-15:00	75%	82%	78%	80%	65%	42%
15:00-16:00	68%	75%	72%	74%	58%	38%
16:00-17:00	55%	62%	58%	60%	45%	25%
17:00-18:00	42%	48%	45%	46%	35%	22%

Low Utilization

High Utilization

Peak: Tue 10:00-12:00 (89.2%)

ROOM UTILIZATION DETAILS

Individual Room Performance Analysis

Room Code	Building	Type	Capacity	Weekly Hours	Utilized Hours	Utilization Rate	Peak Usage	Status
B1.21	Main Building	Classroom	40	45h	32h	71%	Mon 10:00	Optimal
B1.22	Main Building	Classroom	35	45h	28h	62%	Tue 11:00	Optimal
B2.11	Science Building	Classroom	45	45h	25h	56%	Wed 9:00	Balanced
Lab 3	Lab Wing	Computer Lab	30	50h	42h	84%	Thu 10:00	Highly Utilized
A1.12	Annex	Classroom	20	45h	14h	31%	Fri 9:00	Underutilized
B1.25	Main Building	Lecture Hall	60	40h	34h	85%	Mon 11:00	Highly Utilized
Lab 2	Lab Wing	Computer Lab	25	50h	43h	86%	Wed 10:00	Highly Utilized
B3.12	Tech Center	Classroom	40	45h	38h	84%	Thu 11:00	Highly Utilized
A1.08	Annex	Classroom	30	45h	19h	42%	Tue 15:00	Balanced

Showing 1-15 of 86 rooms

SPACE UTILIZATION INSIGHTS

Key Findings & Trends

Technology Center Optimization

82% utilization with balanced daily distribution

Tuesday Morning Peak

89.2% peak utilization creating scheduling bottlenecks

Annex Building Underutilization

58% utilization with 8 rooms consistently below 40%

Computer Lab Demand

94% peak utilization requiring additional lab capacity

Friday Afternoon Gap

45% average utilization on Friday afternoons

SPACE OPTIMIZATION RECOMMENDATIONS

Actionable Insights

Redistribute Tuesday Classes

Move 8 classes from Tuesday peak to underutilized periods

Annex Building Activation

Incentivize departments to use underutilized Annex spaces

Lab Capacity Expansion

Convert 2 standard classrooms to computer labs

Friday Utilization Program

Develop special Friday scheduling incentives

SPACE PLANNING PROJECTIONS

Future Capacity and Facility Planning

Projected Enrollment Growth

+8.2%

Next academic year

Additional Room Capacity Needed

+285

Weekly student-seat hours

Optimal New Rooms

4-6

Based on current utilization patterns

Renovation Priority

High

Annex building technology upgrade

Space Planning Recommendations

Convert B1.15 and B1.18 to computer labs to address 94% lab utilization
Develop Annex building activation plan to increase from 58% to 75% utilization
Plan for 4 new medium-sized classrooms in Technology Center
Implement smart scheduling to better distribute Tuesday peak load
Consider evening program expansion to utilize existing capacity

ACADEMIC ANALYTICS

Attendance Insights

Comprehensive analysis of student attendance patterns, trends, and early warning indicators for academic intervention.

OVERALL ATTENDANCE RATE

92.4%

+1.2% from last week

College-wide average

📊

AT-RISK STUDENTS

+8 from last week

Below 75% attendance

⚠️

CHRONIC ABSENTEEISM

-3 from last week

Missed 30%+ of classes

🚨

PERFECT ATTENDANCE

1,245

+42 from last week

100% attendance rate

⭐

ATTENDANCE TRENDS

Weekly Attendance Rate

Overall Attendance

First Year

Upper Years

Target attendance: 90%+ Current variance: +2.4%

PROGRAM PERFORMANCE

Attendance Rate by Academic Program

Current Attendance

Target (90%)

Information Technology

Computer Science

Business Administration

Education

Arts & Sciences

ATTENDANCE DISTRIBUTION

Student Distribution by Attendance Level

Critical (<60%)

At-Risk (60-75%)

Moderate (75-90%)

Good (90-95%)

Excellent (>95%)

At-Risk Threshold

75%

Critical Threshold

60%

DAILY PATTERNS

Attendance by Day of Week

Friday shows lowest attendance at 88.7%

TIME PATTERNS

Attendance by Class Time

Evening classes show highest consistency

EARLY WARNING SYSTEM

At-Risk Student Indicators

New At-Risk This Week

Students dropped below 75%

Improved This Week

Moved above 75% threshold

Chronic Absenteeism

Consistently below 70%

Intervention Success Rate

68%

Students showing improvement

Student ID	Name	Program	Current Attendance	Trend	Last Intervention	Risk Level
2023-00912	Santos, Juan	BSIT	68%	declining	Nov 15, 2025	High
2024-00119	Reyes, Maria	BSEd	62%	stable	Nov 18, 2025	High
2022-00421	Garcia, Luis	BSBA	71%	improving	Nov 10, 2025	Medium
2023-00765	Tan, Andrea	BSCS	59%	declining	Nov 20, 2025	Critical
2024-00342	Lim, Michael	BSIT	73%	stable	Nov 12, 2025	Medium
2023-00891	Chen, Sophia	BSEd	67%	improving	Nov 16, 2025	High
2022-00567	Ong, David	BSBA	58%	declining	Nov 22, 2025	Critical

SECTION ATTENDANCE DETAILS

Class-Level Attendance Analysis

Section Code	Course	Faculty	Schedule	Enrollment	Avg Attendance	At-Risk Students	Trend	Status
BSIT-3A	Advanced Programming	Dela Cruz	MWF 9:00-10:30	38	94.2%	2	improving	Excellent
BSCS-2B	Data Structures	Rivera	TTh 10:30-12:00	32	93.8%	1	stable	Excellent
BSBA-4A	Strategic Management	Santos	MWF 13:00-14:30	36	91.5%	3	improving	Good
BSEd-1C	Foundations of Education	Chiong	TTh 8:00-9:30	22	90.2%	4	declining	Good
BSIT-1B	Programming 1	Garcia	MWF 14:00-15:30	29	88.7%	6	stable	Moderate
BSCS-3C	Algorithms	Ramos	TTh 13:00-14:30	35	95.1%	0	improving	Excellent
BSBA-2D	Marketing Principles	Lopez	MWF 10:00-11:30	42	89.3%	5	declining	Moderate
BSEd-4A	Teaching Methods	Tan	TTh 15:00-16:30	28	92.8%	2	stable	Good
BSIT-2C	Web Development	Chen	MWF 11:00-12:30	35	93.5%	1	improving	Excellent
BSCS-1A	Intro to CS	Wang	TTh 9:00-10:30	25	87.2%	7	declining	Moderate

Showing 1-15 of 192 sections

ATTENDANCE INSIGHTS

Key Findings & Patterns

Overall Improvement Trend

Colleg attendance increased by 2.4% over past 4 weeks

Friday Attendance Challenge

Friday classes show 3.7% lower attendance than weekly average

First-Year Student Concern

First-year students account for 58% of at-risk attendance cases

Evening Program Success

Evening classes maintain 94.2% attendance rate consistently

Intervention Effectiveness

68% of students show improvement after academic advising

INTERVENTION RECOMMENDATIONS

Actionable Strategies

First-Year Support Program

Develop targeted orientation and mentoring for first-year students

Friday Engagement Initiative

Implement active learning strategies for Friday classes

Early Alert System Enhancement

Improve automated alerts for students approaching risk thresholds

Faculty Training Program

Train faculty on attendance tracking and early intervention strategies

INTERVENTION TRACKING

Active Attendance Intervention Cases

Active Interventions

Ongoing support cases

Completed This Month

Successful interventions

Avg Intervention Duration

3.2

Weeks to improvement

Success Rate

68%

Students reaching 80%+ attendance

Student	Program	Initial Attendance	Current Attendance	Intervention Type	Start Date	Progress	Counselor
Santos, Juan	BSIT	58%	68% (+10%)	Academic Advising	Nov 15, 2025	Improving	Dr. Reyes
Reyes, Maria	BSEd	55%	62% (+7%)	Tutoring Referral	Nov 18, 2025	Stable	Ms. Lim
Garcia, Luis	BSBA	65%	71% (+6%)	Faculty Mentoring	Nov 10, 2025	Significant Improvement	Dr. Torres
Tan, Andrea	BSCS	52%	59% (+7%)	Counseling Session	Nov 20, 2025	Slight Improvement	Mr. Chen
Lim, Michael	BSIT	68%	73% (+5%)	Study Skills Workshop	Nov 12, 2025	Improving	Dr. Reyes

ACADEMIC ANALYTICS

Retention & At-Risk Trends

Comprehensive analysis of student retention patterns, at-risk indicators, and proactive intervention strategies for student success.

OVERALL RETENTION RATE

87.2%

+2.1% from last term

Year-over-year retention

✅

AT-RISK STUDENTS

156

+12 from last month

Multiple risk factors

⚠️

CRITICAL RISK CASES

+3 from last week

High probability of attrition

🚨

INTERVENTION SUCCESS

72%

+5% from last term

At-risk students retained

✅

RETENTION TRENDS

Cohort Retention Over Time

Overall Retention

First-Year Retention

Target

Target retention: 90% Current variance: -2.8%

RISK FACTOR ANALYSIS

Primary At-Risk Indicators

Prevalence

Impact on Retention

PROGRAM PERFORMANCE

Retention by Academic Program

Information Technology

Computer Science

Business Administration

Education

Arts & Sciences

Highest

BSIT: 91.5%

Lowest

BSEd: 82.3%

YEAR LEVEL ANALYSIS

Retention by Academic Year

First Year

Second Year

Third Year

Fourth Year

Graduate

First-year retention critical at 84.2%

INTERVENTION IMPACT

Success Rates by Intervention Type

Academic Advising

Tutoring Programs

Financial Aid Support

Counseling Services

Peer Mentoring

Academic advising shows 78% success rate

EARLY WARNING DASHBOARD

Proactive At-Risk Student Identification

Prediction Accuracy

86.3%

Risk identification model

Early Detection Rate

74%

Identified before midterm

False Positive Rate

8.2%

Low false alarm rate

Model Confidence

High

Based on 3 years of data

Student ID	Name	Program	Risk Score	Primary Risk Factors	Predicted Outcome	Confidence
2023-00912	Santos, Juan	BSIT	87	Low GPA, Attendance <75%	High Risk	92%
2024-00119	Reyes, Maria	BSEd	76	Financial Stress	High Risk	85%
2022-00421	Garcia, Luis	BSBA	92	Multiple Course Failures, Low Attendance	Critical Risk	96%
2023-00765	Tan, Andrea	BSCS	68	Mid-term Grade Decline	Medium Risk	78%
2024-00342	Lim, Michael	BSIT	81	First-generation, Financial Stress	High Risk	88%
2023-00891	Chen, Sophia	BSEd	59	Work Commitments	Low Risk	72%
2022-00567	Ong, David	BSBA	95	Academic Probation, Multiple Risk Factors	Critical Risk	98%

AT-RISK STUDENT REGISTRY

Comprehensive At-Risk Student Tracking

Student ID	Name	Program	Year	Risk Level	Risk Factors	Current GPA	Attendance	Intervention Status
2023-00912	Santos, Juan	BSIT	2nd	High	Academic, Attendance	1.8	68%	Academic Advising
2024-00119	Reyes, Maria	BSEd	1st	Medium	Financial	2.3	82%	Financial Counseling
2022-00421	Garcia, Luis	BSBA	3rd	Critical	Academic, Multiple	1.5	58%	Intensive Support
2023-00765	Tan, Andrea	BSCS	2nd	Medium	Academic	2.1	75%	Tutoring
2024-00342	Lim, Michael	BSIT	1st	High	Financial, First-gen	2	79%	Mentoring
2023-00891	Chen, Sophia	BSEd	2nd	Low	External	2.5	85%	Monitoring
2022-00567	Ong, David	BSBA	3rd	Critical	Academic, Attendance, Multiple	1.2	52%	Case Management

Showing 1-15 of 156 at-risk students

INTERVENTION STRATEGIES

Active Intervention Programs & Progress

Academic Advising

Active cases

78% success rate

Tutoring Programs

Active participants

65% success rate

Financial Aid Support

Active cases

82% success rate

Intervention Program	Target Group	Participants	Start Date	Duration	Success Rate	Budget Utilized	Status
First-Year Success Program	First-year students	120	Aug 2025	8 weeks	72%	₱45,000	Active
Academic Recovery Program	Probation students	45	Sep 2025	12 weeks	65%	₱28,000	Active
STEM Tutoring Initiative	STEM majors	85	Jul 2025	Ongoing	78%	₱52,000	Active
Financial Wellness Program	Financial need	62	Jun 2025	Ongoing	82%	₱35,000	Active
Peer Mentoring Program	First-generation	38	Aug 2025	16 weeks	75%	₱22,000	Planning

RETENTION INSIGHTS

Key Findings & Patterns

First-Year Transition Success

Orientation program shows 15% improvement in first-term retention

Mid-Term Critical Period

42% of attrition occurs between weeks 6-10 of the term

Financial Barriers

28% of at-risk students cite financial stress as primary concern

Academic Preparedness Gap

First-generation students show 12% higher attrition rate

Early Intervention Impact

Students identified and supported before week 4 show 68% higher retention

STRATEGIC RECOMMENDATIONS

Proactive Retention Strategies

Enhanced First-Year Experience

Expand orientation and peer mentoring for first-year students

Mid-Term Check-In System

Implement systematic academic check-ins at week 6

Financial Wellness Program

Develop financial literacy and emergency aid resources

Predictive Analytics Expansion

Enhance early warning system with additional risk factors

RETENTION PROJECTIONS

Future Retention Goals and Targets

Current Retention Rate

87.2%

Academic Year 2024-2025

Next Year Target

89.5%

+2.3% improvement goal

3-Year Strategic Goal

92.0%

Institutional target

Projected Achievement

90.1%

Based on current initiatives

Strategic Initiatives for Retention Improvement

Implement comprehensive first-year experience program targeting 5% retention improvement
Expand academic support services to reach 40% more at-risk students
Develop faculty early alert training program for proactive intervention
Enhance financial aid packaging and emergency support systems
Create peer mentoring program targeting first-generation students
Implement data-driven intervention tracking and success measurement

Student Profile Management

Manage student clearances, applications, and tracking

Pending Clearance

Completed

In Progress

Rejected

Student Clearance Center

Trimester Clearances

Complete clearance after each trimester period

Semester Clearances

Complete clearance after each semester period

Graduation Clearance

For students completing their degrees

My Student Clearance Applications

View All

Graduation Clearance

Application ID: STD-CLR-2023-GRD-042

Current Office

Library

In Progress Submitted: 5 days ago

Progress

60%

2nd Trimester Clearance

Application ID: STD-CLR-2023-T2-128

Certificate

Approved Completed: 2 weeks ago

Progress

100%

Student Clearance Tracking

Student Application ID

Application Status: In Progress

Application ID: STD-CLR-2023-GRD-042

Submitted

Application received

Nov 1

Finance Office

Fees verification completed

Nov 3

Registrar Office

Academic records verified

Nov 5

Library

Checking for outstanding books

Current

Department Head

Pending

Certificate Issuance

Pending

Student Clearance Offices

Finance Office

Fee verification

Completed

Registrar Office

Academic records

Completed

Library

Book returns

In Progress

Department Head

Final approval

Pending