Levelbuilder to staging

dashboard/config/blocks/GamelabJr/gamelab_changeVarBy.js

@@ -0,0 +1,20 @@
+var studentVarToken = false;
+var varLog={};
+
+function changeVarBy(varName, value){
+  for(var b in window) {
+    if(b=="math_random_int") {
+      studentVarToken = false;
+      console.log("...end list");
+    }
+    if(studentVarToken && window.hasOwnProperty(b)) {
+      //console.log(b);
+      varLog[b] = window[b];
+    }
+    if(b=="playSoundOptions") {
+      studentVarToken = true;
+      console.log("Student variables:");
+    }
+  }
+  console.log(varLog);
+}

dashboard/config/blocks/GamelabJr/gamelab_changeVarBy.json

@@ -0,0 +1,23 @@
+{
+  "category": "Validation",
+  "config": {
+    "func": "changeVarBy",
+    "docFunc": "gamelab_changeVarBy",
+    "blockText": "change {VARIABLE} by {VAL}",
+    "color": [
+      312,
+      0.32,
+      0.62
+    ],
+    "args": [
+      {
+        "name": "VARIABLE",
+        "variableInput": true
+      },
+      {
+        "name": "VAL",
+        "type": "Number"
+      }
+    ]
+  }
+}

dashboard/config/courses/csa-2022.course

@@ -1,7 +1,9 @@
 {
   "name": "csa-2022",
   "script_names": [
-    "csa1-2022"
+    "csa1-2022",
+    "csa2-2022",
+    "csa3-2022"
   ],
   "published_state": "in_development",
   "instruction_type": "teacher_led",

dashboard/config/libraries/variableLog.interpreted.js

@@ -0,0 +1,72 @@
+var studentVarToken = false;
+var varLog={};
+
+function updateLog(){
+  var start = Object.keys(window).indexOf("playSoundOptions")+1;
+  var end = Object.keys(window).indexOf("math_random_int");
+  var index;
+  for(var i=start;i<end;i++){
+    if(window[Object.keys(window)[i]] != undefined){
+      varLog[Object.keys(window)[i]] = window[Object.keys(window)[i]];
+    }
+  }
+  varWatchers(varLog);
+
+  if(validationProps){//is Sprite Lab
+    if(!validationProps.previous){
+      validationProps.previous = {};
+    }
+    detectVarChange();
+    validationProps.previous.varLog=JSON.parse(JSON.stringify(varLog));
+  }
+
+}
+
+function varWatchers(varLog){
+  for(var key in varLog){
+    var index = Object.keys(varLog).indexOf(key);
+    var x = 5;
+    var y = 5;
+    watcher(key, varLog[key], index, x, y);
+  }
+}
+
+function watcher(label, value, index, x, y){
+  if(!value&&value!=0&&value!=''){
+    value = 'undefined';
+  }
+  //rect(fontSize/2,fontSize/2+index*fontSize*2);
+  var fontSize=15;
+  textSize(fontSize);
+  textAlign(LEFT,CENTER);
+  labelX = x + 5;
+  valueX = x + 15 + textWidth(label);
+  textY = y + (index+0.5) * fontSize*2;
+  stroke("#c6cacd");
+  fill("#e7e8ea");
+  rect(x,y + index * fontSize*2,textWidth(label)+textWidth(value)+25,fontSize*2, fontSize/2);
+  noStroke();
+  fill("#5b6770");
+  text(label,labelX,textY);
+  fill("#ffa400");
+  rect(valueX - 5,y + (index+0.125) * fontSize*2,textWidth(value)+10,fontSize*1.5, fontSize/1.5);
+  noStroke();
+  fill("white");
+  text(value,valueX,textY);
+}
+
+function detectVarChange(){
+  if(validationProps.previous.varLog){
+    if(JSON.stringify(validationProps.previous.varLog) != JSON.stringify(varLog)){
+      /*for (var key in validationProps.previous.varLog){
+        if(validationProps.previous.varLog[key]!=window[key]){
+          //console.log("["+ World.frameCount + "]: " + key + " changed from " + validationProps.previous.varLog[key] + " to " + window[key]);
+        }
+      }*/
+      return true;
+    }
+  }
+  return false;
+}
+
+other.push(updateLog);

dashboard/config/locales/scripts.en.yml

@@ -23756,13 +23756,13 @@ en:
           description: |-
             This unit is a hands-on introduction to developing a machine learning model with tabular data. Students explore how computers learn from data to make decisions, then develop machine learning projects around real-world data. The unit culminates in designing a machine learning app to solve a personally relevant problem.
 
-            If you are signed in with a Code.org teacher account, links to lesson plans will appear next to each lesson. You can also create a Verified Teachers Account to view answer keys and exemplars - [click here](https://support.code.org/hc/en-us/articles/115001550131-Becoming-a-verified-teacher-CS-Principles-and-CS-Discoveries-only-) to learn more about becoming a Verified Teacher.
-
             This unit assumes students are familiar with App Lab, specifically using Design Mode to create a user interface and using Events to change the screen when clicking a button. [Click Here](https://docs.google.com/document/d/1SkMCN4Eid3-mGoRUQkurQGJqoOJ9PydfB7uGE0xZyFA/preview) to learn more about recommendations for introducing students to App Lab before this unit.
+
+            **Professional Development:** If you are interested in teaching this course, we recommend completing the free [AI/ML Self-Paced Professional Development Module](https://studio.code.org/s/self-paced-pl-csd5-2021). The module is designed to take 2 hours to complete. No previous experience with coding or AI is assumed.
           student_description: |-
             This unit is a hands-on introduction to developing a machine learning model with tabular data. You will explore how computers learn from data to make decisions, then develop machine learning projects around real-world data. The unit culminates in designing a machine learning app to solve a personally relevant problem.
 
-            **For Teachers:** [Click here](https://docs.google.com/document/d/1myJwrDyRlAjwVNDS3gs-3JaJNhogsGMt9Swo-bpySgE/preview#heading=h.c7x6ho8ek6yz) to learn more about this unit and view lesson plans. You can also access lesson plans from this page if you create a Code.org teacher account.
+            **For Teachers:** [Click here](https://studio.code.org/s/aiml-2021?viewAs=Teacher) to see lesson plans and teacher resources for this unit.
           lesson_groups:
             lessonGroup-2:
               display_name: Chapter 1 - Understanding Machine Learning
@@ -23959,9 +23959,11 @@ en:
             **Implementation guidance for Unit 7**
 
             - Complete Unit 1 Chapter 1 before starting this unit
-            - This unit assumes students have seen App Lab from Unit 4: The Design Process before starting the unit. [Click Here](https://docs.google.com/document/d/1SkMCN4Eid3-mGoRUQkurQGJqoOJ9PydfB7uGE0xZyFA/preview) to learn more about the App Lab expectations in this unit, and ways to introduce App Lab to students before starting the unit.
+            - This unit assumes students are familiar with App Lab, specifically using Design Mode to create a user interface and using Events to change the screen when clicking a button. [Click Here](https://docs.google.com/document/d/1SkMCN4Eid3-mGoRUQkurQGJqoOJ9PydfB7uGE0xZyFA/preview) to learn more about recommendations for introducing students to App Lab before this unit.
             - This is an optional unit that can be used in place of another CSD unit - see the [Implementation Guide](https://docs.google.com/document/d/1SkMCN4Eid3-mGoRUQkurQGJqoOJ9PydfB7uGE0xZyFA/preview) for more information
             - You can view the full [Curriculum Guide](https://docs.google.com/document/d/1myJwrDyRlAjwVNDS3gs-3JaJNhogsGMt9Swo-bpySgE/preview) for more information about this unit
+
+            **Professional Development:** If you are interested in teaching this course, we recommend completing the free [AI/ML Self-Paced Professional Development Module](https://studio.code.org/s/self-paced-pl-csd5-2021). The module is designed to take 2 hours to complete. No previous experience with coding or AI is assumed.
           student_description: Unit 7 is a hands-on introduction to developing a machine learning model with tabular data. You will explore how computers learn from data to make decisions, then develop your own machine learning projects around real-world data. The unit culminates with designing your own machine learning app to solve a personally relevant problem.
         kodea-pd-2021:
           title: CSF Online PD - Kodea
@@ -30740,3 +30742,58 @@ en:
           description_short: ''
           description: ''
           student_description: ''
+        pre-express-2022:
+          lessons: {}
+          lesson_groups:
+            csf_sequencing:
+              display_name: Sequencing
+            csf_loops:
+              display_name: Loops
+            csf_events:
+              display_name: Events
+          name: pre-express-2022
+          title: ''
+          description_audience: ''
+          description_short: ''
+          description: ''
+          student_description: ''
+        csa2-2022:
+          lessons:
+            lesson-1:
+              name: Neighborhood Store Management Project – Day 1
+            lesson-2:
+              name: Neighborhood Store Management Project – Day 2
+            lesson-3:
+              name: Neighborhood Store Management Project – Day 3
+            lesson-4:
+              name: FRQ Practice
+            lesson-5:
+              name: Unit 2 Assessment
+          lesson_groups:
+            lessonGroup-2:
+              display_name: Content
+            lessonGroup-3:
+              display_name: Show What You Know
+          name: csa2-2022
+          title: Giving Objects State ('22-'23)
+          description_audience: ''
+          description_short: ''
+          description: ''
+          student_description: ''
+        csa3-2022:
+          lessons:
+            lesson-1:
+              name: FRQ Practice
+            lesson-2:
+              name: Unit 3 Assessment
+          lesson_groups:
+            lessonGroup-2:
+              display_name: Content
+            lessonGroup-3:
+              display_name: Show What You Know
+          name: csa3-2022
+          title: Expanding Program Data ('22-'23)
+          description_audience: ''
+          description_short: ''
+          description: ''
+          student_description: ''