Numeracy and A-level skills comprehensive test - University of Hertfordshire

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Alessandro Palazio 1 month, 2 weeks ago

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Alessandro Palazio 1 month, 3 weeks ago

Created this as a copy of Numeracy and A-level skills test for health science - University of Hertfordshire.

Name	Status	Author	Last Modified
DIAGNOSYS	Ready to use	Christian Lawson-Perfect	19/05/2023 15:59
Numeracy and A-level skills test for health science - University of Hertfordshire	Ready to use	Alessandro Palazio	11/04/2025 12:03
Numeracy and A-level skills comprehensive test - University of Hertfordshire	draft	Alessandro Palazio	01/04/2025 16:47

There are 32 other versions that do you not have access to.

103, Negative Numbers

104, Size of decimals

105, Decimal places

106, Definition of positive powers

107, Ratios

108, Factors of an integer

109, Simple fractions

201, Use of < and > signs

205, Inverse ratios

206, Cancelling numerical fractions

216, Add/subtract numerical fractions

301, Solution of simple inequalities

202, Significant figures

203, Definition of negative powers

204, Rules for positive powers

302, Scientific Notation

303, Simplification of fractions with powers

304, Rules for negative powers

305, Rules for fractional powers

306, Definition of fractional powers

401, Simplify with scientific notation

402b, Log rules

403, Arbitrary factors

110, Collect terms (simple)

111, Solving a simple equation

112, Simple calculation

113, Evaluating a simple expression

207, Multiply algebraic fractions

208, Factors of algebraic products

209, Simple Factorisation

210, Expanding one bracket

211, Collecting terms

212, Solving linear equations

213, Transposition of formula

214, Evaluating formula

215, Precedence Rules

307, Division of algebraic fractions

308, Add/subtract algebraic fractions

309, Simple Quadratic equations

310, Relation between roots and factors

311, Factorising a quadratic

312, Expanding two brackets

313, Difference of squares

314, Simultaneous Equations

315, Unusual linear equation

316, Use of quadratic formula

317, Complex numbers

404, L.c.d. of an algebraic fraction

405, Identification of common errors

406, Solve quad. by comp. the square

407, Quadratics - completing the square

408, Multiplication of complex numbers

410, Substituting into a formula

411, Solutions of a quadratic

412, Difficult linear equation

341, Differentiation of powers

342, Finding Max/Min of a quadratic

343, Geometric Progression

441, Product rule

442, Integration of powers

151, Coordinates

251, Gradient of a straight line

351, Equation of a straight line

451, Recognise formula of quad. graph

452, Recognise formula of recip. graph

221, Pythagoras

222, Definition of sin and cos

223, Percentages

321, Equation of a circle

322, Sin and Cos formula

323, Definition of radians

324, Percentages (advanced)

421, Deduce radius of circle

422, Sin and Cos as functions

161, Area of a triangle

261, Area of trapezium

262, Area and circumference of a circle

263, Similar triangles

361, Volume of cylinder

362, Area/Length relationship

363, Area of irregular shapes

461, Surface area of a cylinder

462, Volume Area Length relationships

231, Range of a set of numbers

232, Mean of a set of numbers

233, Simple probability (coins)

334, Conditional probability

234, Venn Diagrams (probability)

335, Venn Diagrams (conditional prob.)

501, Decomposition of function to partial fractions

502, Solve equation using log

402, Logs definition

442b, Integration of Powers, Trig and Exp

443, Definite Integrals

444, Integration by substitution

505, Integration by parts

341b, Differentiation of polynomials

341c, Differentiation of exponential, log, trig functions

503, Chain rule - powers

504, Quotient rule

240, Poisson Distribution

241, Binomial Distribution

342, Probability Complement rule

606, Forces

605, Forces (easy)

604, Vector magnitude

603, Vectors linear combination

602, Vector addition and scalars

601, Vector between points

505, Chain rule - trigonometry

Diagnostic algorithm

Extend built-in algorithm?

Base diagnostic algorithm

state (Produces the initial value of the state object): // should be renamed "initial_state"
    [
        "topics": map(
            [
                "topic": topic,
                "status": "unknown" // "unknown", "passed", or "failed"
            ],
            topic,
            values(topics)
        ),
        "retries": 3,
        "finished": false,
    ]

topics_by_objective (A dictionary mapping a learning objective name to a list of indices of topics):
    dict(map(
        let(
            ltopics, values(topics),
            indices, filter(lo["name"] in ltopics[j]["learning_objectives"], j, 0..len(ltopics)-1),
            [lo["name"],indices]
        ),
        lo,
        learning_objectives
    ))

unknown_topics (Which topics are still unknown?): 
    map(x["topic"],x,filter(x["status"]="unknown",x,state["topics"]))

first_topic (The first topic to pick a question on):
    unknown_topics[floor(len(unknown_topics)/2)]["name"]

first_question (The first question to show the student):
    random(topics[first_topic]["questions"])

get_dependents (An expression which gets the topics to update after answering a question):
    expression("""
        [target] + flatten(map(eval(get_dependents,["target":t,"correct":correct]),t,topics[target][if(correct,"depends_on","leads_to")]))
    """)

correct (Did the student get the current question right?):
    current_question["credit"]=1

after_answering (Update the state after the student answers a question):
    let(
        ntopics, eval(get_dependents,["target":current_topic,"correct":correct])
    ,   nstate, state + ['topics': map(
                    if(tstate["topic"]["name"] in ntopics, tstate + ["status":if(correct,"passed","failed")], tstate),
                    tstate,
                    state["topics"]
                )]
    , nstate
    )

action_retry (Use up one retry and visit the same topic again):
    [
        "label": translate("diagnostic.use retry"),
        "state": state + ["retries": state["retries"]-1],
        "next_question": random(topics[current_topic]["questions"])
    ]

action_stop (Stop the exam):
    [
        "label": translate("diagnostic.end test"),
        "state": state,
        "next_question": nothing
    ]

action_move_on (Move to the next topic, or end the exam if there are no more):
    let(
        state, after_answering,
        immediate_next_topics, topics[current_topic][if(correct, "leads_to", "depends_on")],
        unknown_topics, map(x["topic"],x,filter(x["status"]="unknown",x,state["topics"])),
        unknown_immediate_topics, filter(x["name"] in immediate_next_topics,x,unknown_topics),
        next_topics, if(len(unknown_immediate_topics), unknown_immediate_topics, unknown_topics),
        finished, len(next_topics)=0 or state["finished"],
        topic,
            if(not finished,
                next_topics[floor(len(next_topics)/2)]["name"]
            ,
                nothing
            ),
        [
            "label": translate("diagnostic.move to next topic"),
            "state": after_answering,
            "next_question": if(not finished, random(topics[topic]["questions"]), nothing)
        ]
    )

can_move_on:
    action_move_on["next_question"]<>nothing

next_actions (Actions to offer to the student when they ask to move on):
    let(
        feedback, retries_feedback+"\n\n"+translate("diagnostic.next step question")
    ,   [
            "feedback": feedback,
            "actions": if(not correct and state["retries"]>0, [action_retry], []) + if(can_move_on,[action_move_on],[action_stop])
        ]
    )

after_exam_ended (Update the state after the exam ends):
    let(
        state, after_answering,
        ntopics, map(t+["status": if(t["status"]="unknown","failed",t["status"])],t,state["topics"]),
        state+["finished": true]
    )

finished (Is the test finished? True if there are no unknown topics):
    len(unknown_topics)=0 or state["finished"]

total_progress:
    let(
        num_topics, len(state["topics"]),
        known, filter(tstate["status"]<>"unknown",tstate,state["topics"]),
        passed, filter(tstate["status"]="passed",tstate,known),
        num_known, len(known),
        num_passed, len(passed),
        [
            "name": translate("control.total"),
            "progress": if(num_topics>0,num_known/num_topics,0), 
            "credit": if(num_known>0,num_passed/num_topics,0)
        ]
    )

learning_objective_progress:
    map(
        let(
            tstates, map(state["topics"][j],j,topics_by_objective[lo["name"]]),
            known, filter(tstate["status"]<>"unknown",tstate,tstates),
            passed, filter(tstate["status"]="passed",tstate,known),
            num_topics, len(tstates),
            num_known, len(known),
            num_passed, len(passed),
            ["name": lo["name"], "progress": if(num_topics>0,num_known/num_topics,0), "credit": if(finished,num_passed/num_topics,if(num_known>0,num_passed/num_known,0))]
        ),
        lo,
        learning_objectives
    )

progress (Progress on each of the learning objectives, plus total progress):
    learning_objective_progress+
    total_progress

retries_feedback:
    translate("diagnostic.now assessing topic", ["current_topic": current_topic]) + " " +
    let(
        retries, state["retries"], 
        pluralise(retries, translate("diagnostic.one retry left"), translate("diagnostic.retries left", ["retries": retries ]))
    )
    + " " +
    let(
        p,total_progress["progress"],
        percentage, dpformat(100p, 0),
        translate("diagnostic.percentage completed", ["percentage": percentage])
    )

weak_objective_threshold (The amount of credit below which a learning objective is considered weak):
    0.6

finished_feedback:
    let(
        weak_objectives, filter(p["credit"]<weak_objective_threshold, p, learning_objective_progress),
    //
        translate("diagnostic.test is over") + " "
        +
        if(len(weak_objectives)=0,
            translate("diagnostic.passed all lo")
        ,
            translate("diagnostic.more work on lo", ["los": 
                join(map(lo["name"], lo, weak_objectives),", ")])
        )
    )

feedback:
    if(finished,
        finished_feedback,
        retries_feedback
    )

Custom diagnostic algorithm

Interface theme

Upload a new theme

Interface language

Allow students to print question content?

Show student's name?

Enter review mode immediately on ending the exam?

	Always	In submitted mode	Only in review mode	Never
Show answer correctness
Show the student's score
Show the maximum score
Show part feedback messages
Show expected answers
Show question advice

Pass threshold

Feedback messages

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Numeracy and A-level skills comprehensive test - University of Hertfordshire

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Taxonomy: mathcentre

Taxonomy: Kind of activity

Taxonomy: Context

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Checkpoint description

Alessandro Palazio 1 month, 2 weeks ago

Alessandro Palazio 1 month, 3 weeks ago

Question groups

101, Multiplication of negative numbers

Topics

Learning objectives

Base diagnostic algorithm

Custom diagnostic algorithm

On leaving a question

On timeout

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