Lord, I Know You Love Me

 

Lord, I Know You Love Me

Lord, I know You love me so,
In highs and lows, in ebb and flow.

Your mercy wakes me every day,
Your grace lights up my darkest way.

Thank You for loving all of me,
Through all my flaws, so patiently.

You’ve seen me stumble, heard my cry,
Yet still You choose to stay nearby.

I’m sorry, Lord, I come again,
With open heart and silent pain.

I always ask for something more,
While blessings gather at my door.

Forgive me when I fail to see,
How rich I am in love from Thee.

I need Your hug, Lord, more than gold,
A place where I can just unfold.

I need Your hug to feel You near,
To wipe away this ache and fear.

Hug me tightly, don’t let go,
In Your arms, I find my glow.

Very tight, Lord, hold me close,
In You I find what I need most.

When the night is long and cold,
Your embrace is my stronghold.

I’ve chased the world, I’ve tried to win,
But found no peace in wealth or sin.

Yet still You call me back again,
With gentle love that knows my name.

Lord, I know You see my heart,
Every broken, shattered part.

You never shame, You never leave,
You comfort all who dare believe.

So here I am, with nothing new,
Just open arms reaching for You.

I’m tired, Lord, of walking blind,
I need Your strength, Your peace of mind.

Hold me close through storm and flame,
Remind me I am not to blame.

Very, very tight, please stay,
Don’t let me drift or slip away.

Let me feel You in my chest,
A holy calm, a place of rest.

Wrap me up in holy grace,
Till joy and tears run down my face.

I need You more than words can say,
Each moment, hour, and weary day.

Thank You, Lord, for loving still—
I rest within Your perfect will

So hug me tightly, Lord divine,
Forever Yours, forever mine.

17 april 25 kamis

 

hospital as tepar

ceitamual

pulsleep

siang maksi dumpling with anisa n novinda

oia no riumburse kudu kuat

anisa dorm as money

pulkulonlina

mlmarimas k index n indolaris n pxmart n tokobuah

allahuakbar

Analyzing "expert questions" statistically

 

Analyzing "expert questions" statistically depends a lot on the type of data you have and what you're trying to find out. Let's break it down and I’ll give you an overview of possible approaches.

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🔍 Step 1: Understand the Question Type

What do you mean by “expert question”? Possibilities:

1. A question written by an expert (e.g., to test others' knowledge)?

2. A question posed to an expert (e.g., in interviews)?

3. A question answered by experts, where you’re evaluating the quality/consistency?

4. A survey question labeled as “expert-level”?

Once that’s clear, you can move to…

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📊 Step 2: Collect the Right Data

Typical data points could include:

• Difficulty ratings (from a panel or AI)

• Number of correct answers by non-experts

• Time taken to answer

• Agreement among experts

• Textual features (e.g., length, keywords, jargon density)

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📐 Step 3: Statistical Methods You Can Use

Here are some methods depending on what you’re analyzing:

A. Descriptive Statistics

To describe the question characteristics:

• Mean, median, SD of difficulty rating

• Frequency of topic types

• Length of question (word count, sentence complexity)

B. Inter-Rater Reliability

If multiple experts rate the same question:

• Cohen’s Kappa (for 2 raters)

• Fleiss’ Kappa (for 3+ raters)

• ICC (Intraclass Correlation Coefficient) if ratings are on a continuous scale

C. Item Analysis (common in education/testing)

Used to evaluate questions in a test:

• Difficulty index (p-value): % of people who answered it correctly

• Discrimination index: Correlation between the item score and total score

• Point-biserial correlation

D. Inferential Statistics

If you want to compare groups (e.g., expert vs non-expert responses):

• t-test / ANOVA: compare mean ratings or performance

• Chi-square test: compare distributions (e.g., topic frequency)

• Regression Analysis: predict difficulty or accuracy based on features of the question

E. Text Analysis + Statistics

If you're analyzing the question text itself:

• Use text mining to extract features (TF-IDF, readability scores)

• Then apply clustering, factor analysis, or logistic regression to relate these to outcomes (like answer accuracy or expert agreement)

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🧠 Example Use Case

You have 50 expert-written questions and 100 learners answering them. You want to know which questions are too easy or too hard.

• Calculate p-value (difficulty index) for each question

• Use discrimination index to see which questions best separate high- and low-performing learners

• Use item-total correlation to flag bad items

• Optional: run a factor analysis to see if items group by topic or skill

Designing a Delphi questionnaire for elementary school teachers

 

Designing a Delphi questionnaire for elementary school teachers involves careful planning to ensure that expert opinions are gathered systematically and refined over multiple rounds. Here's a step-by-step guide tailored to your context:

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🎯 Purpose Clarification

Start by defining the main objective of your Delphi study.
Example: To identify key competencies elementary school teachers need for effective online teaching.

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🧩 Step-by-Step Design

1. Panel Selection (Experts)

• Choose elementary school teachers with:

  • At least 5 years of teaching experience.

  • Involvement in curriculum development or teacher training (if possible).

  • A range of geographic locations or school types (public/private) for diversity.

2. Round 1 – Open-ended Questionnaire

• Purpose: Explore broad opinions.

• Format: Open-ended questions to gather qualitative data.

• Sample questions:

  • “What are the most important skills an elementary school teacher should have today?”

  • “What challenges do you face in implementing innovative teaching methods?”

  • “What professional development topics do you find most useful?”

Tips: Keep it concise and easy to understand for busy teachers.

3. Data Analysis After Round 1

• Use thematic analysis or content analysis to identify key themes or categories.

• Group similar responses to create items for the next round.

4. Round 2 – Structured Questionnaire

• Purpose: Get consensus on themes.

• Format: Likert-scale or ranking questions.

  • Example: “Rate the importance of the following competencies on a scale of 1 (not important) to 5 (very important).”

• Include an optional comment field for clarification.

5. Data Analysis After Round 2

• Calculate measures like median, mean, interquartile range (IQR) for consensus.

• Decide on a cut-off point for consensus (e.g., 75% agreement).

6. Round 3 – Feedback and Re-rating

• Purpose: Confirm or refine consensus.

• Format: Present summarized group responses from Round 2 and ask participants to re-rate.

  • Example: “In Round 2, 80% rated this item as ‘very important.’ Do you agree with this rating?”

• Option to keep or revise responses based on feedback.

7. (Optional) Round 4

• Only if needed, to clarify unclear areas or finalize a priority list.

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✅ Design Tips

• Keep language simple and jargon-free.

• Pilot your questionnaire with 1–2 teachers if possible.

• Use online tools (e.g., Google Forms, SurveyMonkey, Qualtrics) for easy access and analysis.

• Ensure anonymity to reduce bias.

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🧠 Sample Study Ideas (Elementary Teachers)

• Identifying essential 21st-century teaching skills.

• Prioritizing inclusive education strategies.

• Developing effective literacy programs.

• Integrating technology into early education.

The Delphi method

 

The Delphi method is a structured, iterative process used to gather expert opinions and achieve consensus on a specific topic. When applied to competency analysis for a specific occupation like elementary school teacher, it can help identify the key competencies required for effective performance in that role. Here's how it can be applied, along with the principles of the method:

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🔍 Overview: Delphi Method for Competency Analysis (Elementary School Teacher)

1. Purpose:

To identify and validate the core competencies—knowledge, skills, and attitudes—essential for elementary school teachers through expert consensus.

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🧭 Step-by-Step Application

Step 1: Define the Scope and Objective

• Objective: To determine the essential competencies of elementary school teachers (e.g., pedagogical skills, classroom management, emotional intelligence).

• Participants: Select a panel of experts—experienced teachers, principals, teacher trainers, curriculum developers, and education policymakers.

Step 2: First Round – Open-ended Questionnaire

• Experts are asked open questions like:

  • "What competencies do you believe are essential for an elementary school teacher?"

  • "What skills should a teacher have to effectively manage a classroom?"

• Goal: Collect a wide range of ideas and perspectives.

Step 3: Data Analysis

• Responses are categorized and synthesized into a comprehensive list of competencies.

• Redundant or overlapping items are grouped.

Step 4: Second Round – Rating or Ranking

• Experts are given a structured questionnaire with the list of competencies from Round 1.

• They are asked to rate (e.g., on a Likert scale) or rank the importance of each competency.

Step 5: Feedback and Iteration

• Aggregate results are shared with the panel (e.g., mean scores, areas of agreement/disagreement).

• Experts are asked to reconsider their responses in light of group trends.

• This continues for 2–3 rounds until consensus is reached.

Step 6: Final Competency Framework

• A refined and prioritized list of competencies is finalized.

• These competencies can be grouped under domains such as:

  • Instructional Competence

  • Classroom Management

  • Assessment Literacy

  • Emotional and Social Intelligence

  • Ethical and Professional Conduct

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📌 Key Principles of Delphi Method Applied

Principle	Application in Context
Anonymity	Experts give opinions independently, reducing influence or bias.
Iteration	Several rounds allow experts to refine their views.
Controlled Feedback	Summarized results are shared without revealing identities.
Statistical Aggregation	Quantitative data (ratings) supports decision-making.

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✅ Benefits for Elementary Teacher Competency Analysis

• Draws from diverse, experienced perspectives.

• Builds a validated, evidence-based framework for teacher training, recruitment, and evaluation.

• Ensures that the competencies are contextually relevant (e.g., to Indonesian primary education).

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