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How Do We Assess Students?
Quiz by Amy Nielson
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We found you were making a quiz on the subject of "What is a rubric? A tool comprising a set of criteria (with possible levels of performance quality on the criteria) developed to assess learnersâ work, from written to oral to visual. It is used tomeasureperformance,suchastheprocess of doing something (e.g.,playing a musical instrument, making a speech) or products of the learnersâ work (e.g., concept map, laboratory report, bookshelf) (Brookhart, 2013). BENEFITS OF USING RUBRICS Support authentic assessment Reflects how well learners are able to apply knowledge inthe real-world context. Communicate expectations Gives learners an idea of what is expected of them. It is especially useful when the rubrics are communicated to the learners before they are assessed. Improve performance Explicit criteria and performance level descriptions allow learners to understand the desired performance. Learners are able to assess themselves by referring to the specific criteria and performance-level descriptions. Provide informative feedback Instructors are able to provide constructive feedback to learners on their weaknesses and strengths. Promote thinking andlearning 4 Provide informative feedback Instructors are able to provide constructive feedback to learners on their weaknesses and strengths. Learners are able to review and revise their work,thus reflecting on their learning experiences. Ensure fairness Learner performance assessed fairly given its objectivity. It helps avoid disputes between learners and instructors about the scores/grades achieved. TYPES OF RUBRIC ANALYTIC It consists of individual criterion with corresponding descriptor of performance. HOLISTIC It consists of performance descriptors that are placed together to refeclet to overalll performance. ANATOMY OF ANANALYTIC RUBRIC Rating scales with corresponding scores or weights The row represents the criteria for the desired performance, while the column represents the evaluation score. Under the rating scale (corresponding weights orscorescanbeassigned),theperformance descriptors are explicitly stated ANATOMYOF AHOLISTICRUBRIC Descriptions: It comprises the rating scale (corresponding weights or scores can be assigned) in the row while the combined desired performance descriptors are placed in the column. Description of the task The purpose of the assignment is to assess learnerâs cognitive and analytic skills in applying knowledge gained and constructed throughout the course Diffusion of Innovation,bywatching the Surrogates movieand writing ananalytical review of the movie in the context of innovation diffusion.Iwant to provide learners with informative feedback on their cognitive and analytic skills such as the following: applying the concepts of innovation diffusion,making judgmentson the scenes related to innovation diffusion identified from the movie,selecting and critiquing theories of innovation diffusion and making connections between the theories,aswell asarguingand proposing necessary solutions to the problemss hown in the movie. ESTABLISHING ALTERNATIVEASSESSMENTINHIGHEREDUCATION VALIDITYAND RELIABILITYOF RUBRICS. Validity Measuring what is supossedto be measured. Reability Yielding consists results. Instruments that are used in the alternative assessment must be aligned to the learning outcomes and measure well what it intends to measure (valid) and produce consistent scores (reliable). The valid instrument will manifest the true ability (latent trait) of learners and permit appropriate inferences to be made about a specific group of people for specific purposes. TYPES OF VALIDITY FACE VALIDITY Simple form of validity thatapplies a superficial and subjective assessment whether the instrument measures what it is supposed to measure. CONTENT VALIDITY Refers to the extent to which the items on a measure assess the same content or how wellthe content material was sampled inthe measure. CONSTRUCT VALIDITY Refers to the extent to which the test may be said to measure a theoretical construct or trait. CONCURRENT VALIDITY Refers to the extent to which scores onanewmeasure are related to scores from a criterion measure administered at the same time. PREDICTIVE VALIDITY Refers to the uses of the scores from the new measure to predict performance on a criterion measure administered ata later time. STEPS TO CONSIDER WHEN ESTABLISHING CONTENT VALIDITY Calculate the level of expert agreeement for the content validity, get expert to verfy. Interview the expert ,make meta contentdata anĂĄlisis from literatura. STEPS TO CONSIDER WHEN ESTABLISHING CONSTRUCCT VALIDITY Administer the instrument for alll learners, revise any item necccesay, run an apropriates statistical analiysis, administerthe instrument to learners as a pilot test . CONSTRUCTMAP Morepreciseconceptthan construct. Ranges from one extreme to another(fromhightolow,small tolarge,positivetonegative,or strongtoweak). Identifiesthepositionofthe respondentsinthisrange. Representativenessofsampling (questions and ability of respondents). EXAMPLEO FACONSTRUCTMAP:AFFECTIVE LEVELOF AFFECTIVE VARIABLES EXAMPLESOFITEMSIN MEASURINGTEAM WORKING SKILLS 5. Characterisation Learnersvolunteerstodothe groupworks. 4. Organisation Learners are willing to help others,althoughitisnottheir scopeoftask. 3. Valuing Learners respect other team membersâopinionwhendoing thediscussion. 2. Responding Learnergivescooperationwhen neededingroupworks. 1. Receiving Learneracceptsthediversityof races and nationalities among groupmembers. EXAMPLEOFACONSTRUCTMAP:PSYCHOMOTOR LEVELOF PSYCHOMOTOR VARIABLES EXAMPLESOFITEMSIN MEASURING DIGITAL SKILLS 7.Origination Learnerscanmodifytheirowndevicesto performbetter. 6.Adaptation Learnerscansolveandtroubleshootthe problemwhileusingthecomputer. 5.ComplexOvertResponse Learnerscanusethecomputercompetently. 4.Mechanism Learners can use the computer independently,butstillmakeminorerrors. 3.GuidedResponses Learnerscanusethecomputer,butstill needguidance. 2.Set Learnersarereadytousethecomputer. 1.Perception Learnerscanobservehowtousecomputer. EXAMPLEOFACONSTRUCTMAP:COGNITIVE LEVELOF COGNITIV E VARIABLES EXAMPLESOFITEMS IN MEASURING THINKINGSKILLS 6. Creating Learners are able to suggest anewmodelorframeworkof learningdigitalcommunity. 5. Evaluating Learners are able to judge the impactofthescenariotowards educationperspective. 4. Analysing Learnerscandifferentiate the factsusingafew theories. 3. Applying Learnerscansolveproblems usingthefactsgiven. 2. Understanding Learnersareabletoexplainthe factsusingtheirownwords. 1. Remembering Learnersonlymemorisethe. Direction of Increasing âXâ Learners Learners with high âXâ Learners with mid range âXâ Learners with low âXâ Responses to Item Item response indicate highest level of X Item response indicate higher level of X Item response indicate lower level of X The construct map shows the lower ability students are in line with the lower level of items. This shows that when educators plan to develop an instrument, it Item response indicate lowest level of X Direction of Decreasing âXâ is crucial to create an item difficulty thatrepresents learnersâ ability. Learnersâ ability Learners who engage in level characterisation Learners who engage in level organisation Learners who engage in level valuing Learners who engage in level responding Learners who engage in level receiving Direction of DecreasingâXâ MEASURINGCONSTRUCTVALIDITY Unlike content validity, this construct validity can be analysed using statistical analysis. Use Exploratory FactorAnalysis [EFA], Confirmatory FactorAnalysis [CFA] or Unidimensionality to confirm all items are measuring the right construct and the raw variance explained for the latent variables is sufficient. Gap initem map also can show accuracy in construct validity. RELIABILITY The degree to which test scores are consistent over repeated administrations of the same/ equivalent test and therefore considered dependable and repeatable for an individual learner.A test thatproduces highly consistent and stable results (i.e. relative free from random error) is said to be highly reliable. TYPESOFRELIABILITY Test-retest demonstrates the stability of a measure over time 01 Internal consistency most of the items within a rating scale of a concept show consistency of scoring. Inter-rater the extent to which two or more independent raters are consistent in observing, recording and scoring data (should be 70% or higher agreement) 04 Intra-rater relies on one rater to rate an object or event twice (70% or higher of agreement) FACTORSAFFECTING VALIDITYANDHOWTO INCREASEVALIDITY? FACTORS AFFECTING VALIDITY HOWTO INCREASE VALIDITY? 1. Inaccuracy of items in measuringtheoutcomes 1. Vetting session to get reviewsfromtheexpert. 2. Pooritemsdevelopment 2. Followtheformatandtips indevelopinggooditems. 3. Unclearinstructions 3. Do pilot testing to measuretheusabilityof thetest. 4. Interveningevents 4. Controltheinternalthreats validityfactors. 5. Itemsdifficultyisnot suitableforthelearners 5. Create a construct map toensurethereisanitem thatrepresentslearners ability. FACTORS AFFECTING RELIABILIT Y HOWTOINCREASERELIABILITY? 1. TestLength 1. Thetestlengthshouldbeappropriate withtestdifficulty. 2. Test retest interval 2. Suggesteddurationisbetween3 weeksto2months. 3. Variability of scores 3. Doconstructmaptoensuretheitems aresuitablewithlearnersâability. 4. Guessing 4. Penalisetheguessinganswers.You alsocandetecteitherthelearnersare guessing or not using the statistical analysis named guessing analysis andpersonfitanalysis. 5. Inconsistency score from different raters 5. Appointtheratertomarkcertain questionsforalllearners(Thisalways happen when you have more than onesectionandhavemorethanone lecturer). CONCLUSION Coming back to the issue of validity and reliability in assessment, there is a need for educators to put an effort to ensurethattheitemsintheformofquestionsorinstructions arenotonlyclearbutalsoabletomeasurewhatitisintended tomeasurebasedontherelatedlearningoutcomes. Establishingvalidityandreliabilityofinstrumentscan provide educators with some indications of the quality of the measuring tools being used. Valid and reliable instruments enabletheeducatorstocontinuouslyusethemeasuringtools withoutreservation. Reliablenot valid Precisenot Accurate Reliableand valid Preciseand Accurate NotReliable butvalid NotPrecisebut Accurate NotReliable butNotvalid NotPrecisebut NotAccurate 94 ". Would you like to continue making it or start afresh?Why and how do we assess?*1. What is the primary objective of Step 3 in the adolescent health program development process?* a) To gather evidence for situational analysis. b) To decide on the priority issues and behaviors for the program. c) To implement interventions for various health problems. d) To assess the effectiveness of the program. *Answer: b) To decide on the priority issues and behaviors for the program.* *2. What key question is addressed in this step regarding health problems and resources?* a) How many resources can be allocated to each health problem? b) How many health problems can be addressed given the available resources? c) Which health problems have the highest prevalence in the community? d) How do we measure the success of the program? *Answer: b) How many health problems can be addressed given the available resources?* *3. Why is it necessary to prioritize health outcomes for the adolescent program?* a) To ensure that all health problems are addressed simultaneously. b) To accommodate the preferences of community leaders. c) Due to limited resources, focusing on the most immediate needs of adolescents is crucial. d) To align with evidence gathered during the situational analysis. *Answer: c) Due to limited resources, focusing on the most immediate needs of adolescents is crucial.* *4. How does the worksheet help in prioritizing health outcomes for the adolescent program?* a) By providing a list of health problems without any scoring system. b) By assigning equal scores to all health problems. c) By listing general health outcomes and specific health problems with a scoring system. d) By excluding the opinions of adolescents and community leaders. *Answer: c) By listing general health outcomes and specific health problems with a scoring system.* *5. What does the example on the prioritization worksheet illustrate about early pregnancy?* a) It is a low priority health problem. b) It has a low magnitude of the problem. c) It has a moderate level of importance in the community. d) It is the highest priority health problem with a score of 6. *Answer: d) It is the highest priority health problem with a score of 6.* *6. What does a SMART health status objective entail in the context of adolescent health program development?* a) It is a short-term outcome without specific indicators. b) It focuses solely on individual behaviors without considering community perspectives. c) It is specific, measurable, attainable, realistic, and time-bound. d) It does not require baseline data or target year for achievement. *Answer: c) It is specific, measurable, attainable, realistic, and time-bound.*âThereâs No Such Thing as Sound Scienceâ by By Christie Aschwanden was a lead science writer for FiveThirtyEight. FiveThirtyEight, Science, Dec. 6, 2017 Science is being turned against itself. For decades, its twin ideals of transparency and rigor have been weaponized by those who disagree with results produced by the scientific method. Under the Trump administration, that fight has ramped up again. In a move ostensibly meant to reduce conflicts of interest, Environmental Protection Agency Administrator Scott Pruitt has removed a number of scientists from advisory panels and replaced some of them with representatives from industries that the agency regulates. Like many in the Trump administration, Pruitt has also cast doubt on the reliability of climate science. For instance, in an interview with CNBC, Pruitt said that âmeasuring with precision human activity on the climate is something very challenging to do.â Similarly, Trumpâs pick to head NASA, an agency that oversees a large portion the nationâs climate research, has insisted that research into human influence on climate lacks certainty, and he falsely claimed that âglobal temperatures stopped rising 10 years ago.â Kathleen Hartnett White, Trumpâs nominee to head the White House Council on Environmental Quality, said in a Senate hearing last month that she thinks we âneed to have more precise explanations of the human role and the natural roleâ in climate change. The same entreaties crop up again and again: We need to root out conflicts. We need more precise evidence. What makes these arguments so powerful is that they sound quite similar to the points raised by proponents of a very different call for change thatâs coming from within science. This other movement strives to produce more robust, reproducible findings. Despite having dissimilar goals, the two forces espouse principles that look surprisingly alike: Science needs to be transparent. Results and methods should be openly shared so that outside researchers can independently reproduce and validate them. The methods used to collect and analyze data should be rigorous and clear, and conclusions must be supported by evidence. These are the arguments underlying an âopen scienceâ reform movement that was created, in part, as a response to a âreproducibility crisisâ that has struck some fields of science.1 But theyâre also used as talking points by politicians who are working to make it more difficult for the EPA and other federal agencies to use science in their regulatory decision-making, under the guise of basing policy on âsound science.â Scienceâs virtues are being wielded against it. What distinguishes the two calls for transparency is intent: Whereas the âopen scienceâ movement aims to make science more reliable, reproducible and robust, proponents of âsound scienceâ have historically worked to amplify uncertainty, create doubt and undermine scientific discoveries that threaten their interests. âOur criticisms are founded in a confidence in science,â said Steven Goodman, co-director of the Meta-Research Innovation Center at Stanford and a proponent of open science. âThatâs a fundamental difference â weâre critiquing science to make it better. Others are critiquing it to devalue the approach itself.â Calls to base public policy on âsound scienceâ seem unassailable if you donât know the termâs history. The phrase was adopted by the tobacco industry in the 1990s to counteract mounting evidence linking secondhand smoke to cancer. A 1992 Environmental Protection Agency report identified secondhand smoke as a human carcinogen, and Philip Morris responded by launching an initiative to promote what it called âsound science.â In an internal memo, Philip Morris vice president of corporate affairs Ellen Merlo wrote that the program was designed to âdiscredit the EPA report,â âprevent states and cities, as well as businesses from passing smoking bansâ and âproactivelyâ pass legislation to help their cause. The sound science tactic exploits a fundamental feature of the scientific process: Science does not produce absolute certainty. Contrary to how itâs sometimes represented to the public, science is not a magic wand that turns everything it touches to truth. Instead, itâs a process of uncertainty reduction, much like a game of 20 Questions. Any given study can rarely answer more than one question at a time, and each study usually raises a bunch of new questions in the process of answering old ones. âScience is a process rather than an answer,â said psychologist Alison Ledgerwood of the University of California, Davis. Every answer is provisional and subject to change in the face of new evidence. Itâs not entirely correct to say that âthis study proves this fact,â Ledgerwood said. âWe should be talking instead about how science increases or decreases our confidence in something.â The tobacco industryâs brilliant tactic was to turn this baked-in uncertainty against the scientific enterprise itself. While insisting that they merely wanted to ensure that public policy was based on sound science, tobacco companies defined the term in a way that ensured that no science could ever be sound enough. The only sound science was certain science, which is an impossible standard to achieve. âDoubt is our product,â wrote one employee of the Brown & Williamson tobacco company in a 1969 internal memo. The note went on to say that doubt âis the best means of competing with the âbody of factââ and âestablishing a controversy.â These strategies for undermining inconvenient science were so effective that theyâve served as a sort of playbook for industry interests ever since, said Stanford University science historian Robert Proctor. The sound science push is no longer just Philip Morris sowing doubt about the links between cigarettes and cancer. Itâs also a 1998 action plan by the American Petroleum Institute, Chevron and Exxon Mobil to âinstall uncertaintyâ about the link between greenhouse gas emissions and climate change. Itâs industry-funded groupsâ late-1990s effort to question the science the EPA was using to set fine-particle-pollution air-quality standards that the industry didnât want. And then there was the more recent effort by Dow Chemical to insist on more scientific certainty before banning a pesticide that the EPAâs scientists had deemed risky to children. Now comes a move by the Trump administrationâs EPA to repeal a 2015 rule on wetlands protection by disregarding particular studies. (To name just a few examples.) Doubt merchants arenât pushing for knowledge, theyâre practicing what Proctor has dubbed âagnogenesisâ â the intentional manufacture of ignorance. This ignorance isnât simply the absence of knowing something; itâs a lack of comprehension deliberately created by agents who donât want you to know, Proctor said.2 In the hands of doubt-makers, transparency becomes a rhetorical move. âItâs really difficult as a scientist or policy maker to make a stand against transparency and openness, because well, who would be against it?â said Karen Levy, researcher on information science at Cornell University. But at the same time, âyou can couch everything in the language of transparency and it becomes a powerful weapon.â For instance, when the EPA was preparing to set new limits on particulate pollution in the 1990s, industry groups pushed back against the research and demanded access to primary data (including records that researchers had promised participants would remain confidential) and a reanalysis of the evidence. Their calls succeeded and a new analysis was performed. The reanalysis essentially confirmed the original conclusions, but the process of conducting it delayed the implementation of regulations and cost researchers time and money. Delay is a time-tested strategy. âGridlock is the greatest friend a global warming skeptic has,â said Marc Morano, a prominent critic of global warming research and the executive director of ClimateDepot.com, in the documentary âMerchants of Doubtâ (based on the book by the same name). Moranoâs site is a project of the Committee for a Constructive Tomorrow, which has received funding from the oil and gas industry. âWeâre the negative force. Weâre just trying to stop stuff.â Some of these ploys are getting a fresh boost from Congress. The Data Quality Act (also known as the Information Quality Act) was reportedly written by an industry lobbyist and quietly passed as part of an appropriations bill in 2000. The rule mandates that federal agencies ensure the âquality, objectivity, utility, and integrity of informationâ that they disseminate, though it does little to define what these terms mean. The law also provides a mechanism for citizens and groups to challenge information that they deem inaccurate, including science that they disagree with. âIt was passed in this very quiet way with no explicit debate about it â that should tell you a lot about the real goals,â Levy said. But whatâs most telling about the Data Quality Act is how itâs been used, Levy said. A 2004 Washington Post analysis found that in the 20 months following its implementation, the act was repeatedly used by industry groups to push back against proposed regulations and bog down the decision-making process. Instead of deploying transparency as a fundamental principle that applies to all science, these interests have used transparency as a weapon to attack very particular findings that they would like to eradicate. Now Congress is considering another way to legislate how science is used. The Honest Act, a bill sponsored by Rep. Lamar Smith of Texas,3 is another example of what Levy calls a âTrojan horseâ law that uses the language of transparency as a cover to achieve other political goals. Smithâs legislation would severely limit the kind of evidence the EPA could use for decision-making. Only studies whose raw data and computer codes were publicly available would be allowed for consideration. That might sound perfectly reasonable, and in many cases it is, Goodman said. But sometimes there are good reasons why researchers canât conform to these rules, like when the data contains confidential or sensitive medical information.4 Critics, which include more than a dozen scientific organizations, argue that, in practice, the rules would prevent many studies from being considered in EPA reviews.5 It might seem like an easy task to sort good science from bad, but in reality itâs not so simple. âThereâs a misplaced idea that we can definitively distinguish the good from the not-good science, but itâs all a matter of degree,â said Brian Nosek, executive director of the Center for Open Science. âThere is no perfect study.â Requiring regulators to wait until they have (nonexistent) perfect evidence is essentially âa way of saying, âWe donât want to use evidence for our decision-making,ââ Nosek said. Most scientific controversies arenât about science at all, and once the sides are drawn, more data is unlikely to bring opponents into agreement. Michael Carolan, who researches the sociology of technology and scientific knowledge at Colorado State University, wrote in a 2008 paper about why objective knowledge is not enough to resolve environmental controversies. âWhile these controversies may appear on the surface to rest on disputed questions of fact, beneath often reside differing positions of value; values that can give shape to differing understandings of what âthe factsâ are.â Whatâs needed in these cases isnât more or better science, but mechanisms to bring those hidden values to the forefront of the discussion so that they can be debated transparently. âAs long as we continue down this unabashedly naive road about what science is, and what it is capable of doing, we will continue to fail to reach any sort of meaningful consensus on these matters,â Carolan writes. The dispute over tobacco was never about the science of cigarettesâ link to cancer. It was about whether companies have the right to sell dangerous products and, if so, what obligations they have to the consumers who purchased them. Similarly, the debate over climate change isnât about whether our planet is heating, but about how much responsibility each country and person bears for stopping it. While researching her book âMerchants of Doubt,â science historian Naomi Oreskes found that some of the same people who were defending the tobacco industry as scientific experts were also receiving industry money to deny the role of human activity in global warming. What these issues had in common, she realized, was that they all involved the need for government action. âNone of this is about the science. All of this is a political debate about the role of government,â she said in the documentary. These controversies are really about values, not scientific facts, and acknowledging that would allow us to have more truthful and productive debates. What would that look like in practice? Instead of cherry-picking evidence to support a particular view (and insisting that the science points to a desired action), the various sides could lay out the values they are using to assess the evidence. For instance, in Europe, many decisions are guided by the precautionary principle â a system that values caution in the face of uncertainty and says that when the risks are unclear, it should be up to industries to show that their products and processes are not harmful, rather than requiring the government to prove that they are harmful before they can be regulated. By contrast, U.S. agencies tend to wait for strong evidence of harm before issuing regulations. Both approaches have critics, but the difference between them comes down to priorities: Is it better to exercise caution at the risk of burdening companies and perhaps the economy, or is it more important to avoid potential economic downsides even if it means that sometimes a harmful product or industrial process goes unregulated? In other words, under what circumstances do we agree to act on a risk? How certain do we need to be that the risk is real, and how many people would need to be at risk, and how costly is it to reduce that risk? Those are moral questions, not scientific ones, and openly discussing and identifying these kinds of judgment calls would lead to a more honest debate. Science matters, and we need to do it as rigorously as possible. But science canât tell us how risky is too risky to allow products like cigarettes or potentially harmful pesticides to be sold â those are value judgements that only humans can make.Write 5 multiple choice questions for the following transcript ...Setting goals and budgeting. [tranquil music] Getting where you want to be involves three important skills. Setting realistic goals, knowing your net worth, and budgeting. [energetic music] Setting goals is a way to get control of your life. A goal is not the same as a dream. It's not pie in the sky stuff. It's something that's achievable and it comes with a time frame. If you have a big goal, like buying a house in five years' time, you might need a plan that involves a whole series of mini goals to get you there in stages. The important is finding something you know you can do. Most people find longterm goals hard to stick to. Don't worry about it. If 10 years seems too far away, set your horizons a little closer. Give yourself a set sum of money to save in the next few years. You can use it as a springboard to get to your next goal and it'll get you in the savings habit. Changes in your life circumstances may also affect your goal, so use this opportunity to review them. Think about your financial goals when you have some quiet time. It may sound a little obsessive, but write down what they are and how you're going to achieve them. Be specific, be realistic, and always, always keep your goals within reach. Achieving a goal is a great excuse to celebrate, so don't forget to reward yourself for your achievement. [energetic music] Imagine if tomorrow you had to sell everything you own and pay off everything you owe the bank or anyone else, would you be left with much? Would you be left with anything? That figure is called your net worth. It's a measure of your actual financial wealth and growing it over time is what getting sorted is all about. Use Sorted's net work calculator to find out where you're at. Decide what you want your net worth to be in a year's time. Think about your cash and other assets and work out how you might get there. Monitoring and growing your net worth over time is the thing that will eventually get you to retirement in good shape. [energetic music] Budgeting is another one of those, I can't believe I didn't do something so basic, type of things. Do a budget. Stick to it and you're in control. There are two approaches to budgeting. The first is what we call cold turkey. Each time you get paid, you work out what you need to pay for all your essentials. Use Sorted's budget calculator to do this. You then take the rest and put it straight into savings. Going cold turkey on all those other things that you usually throw your money away on. Be realistic with your savings. Don't be too hard on yourself as it could take time for you to get into the saving habit. But if you remove the temptation to spend, you'll improve your financial position each month. If that seems a bit rigorous, try the alternative nip and tick approach. Do a budget using Sorted's budget calculator and then take a hard look at where your money's going. We're prepared to bet there's a nip here and a tuck there that will result in savings and every month you save, you increase your net worth. So go to it. ChatGPT What are the three important skills needed to achieve your financial goals? A) Budgeting, investing, and saving B) Setting realistic goals, knowing your net worth, and budgeting C) Planning, tracking, and monitoring How can you make a big goal more achievable? A) By dreaming about it often B) By breaking it down into a series of mini goals C) By setting a longer time frame What is net worth? A) The amount of money you have in savings B) The value of everything you own minus what you owe C) The amount of money you earn each year What are the two approaches to budgeting mentioned in the transcript? A) Cold turkey and warm turkey B) Nip and tuck and cold turkey C) Nip and tick and warm turkey How can you increase your net worth every month? A) By dreaming about your financial goals B) By sticking to a budget and removing the temptation to spend C) By investing in high-risk stocks How do we become ill? How do we pay for things?How do we keep clean?