Balancing Cost Control and Revenue Growth

Balancing Cost Control and Revenue Growth

Overview of Medical Coding and Its Role in Healthcare Payment Systems

Medical coding stands as a pivotal component within the intricate framework of healthcare revenue cycle management. It plays an essential role in ensuring that healthcare providers can effectively balance cost control while fostering revenue growth. Proper staffing leads to improved resource utilization in medical environments elite medical staffing income statement. This delicate equilibrium is crucial for maintaining the financial health and sustainability of healthcare institutions.


At its core, medical coding involves translating complex medical diagnoses, procedures, and treatments into standardized alphanumeric codes. These codes are used universally to facilitate billing processes and ensure accurate reimbursement from insurance companies and government programs. The precision of this translation directly impacts the financial dynamics of a healthcare facility.


One of the primary advantages of effective medical coding is its contribution to cost control. By providing a clear and standardized language for reporting medical services, it minimizes errors in billing, reduces claim denials, and decreases administrative overheads associated with correcting mistakes. Accurate coding ensures that every service rendered by a healthcare provider is appropriately documented and billed, preventing revenue losses due to underbilling or incorrect coding practices.


Moreover, the role of medical coding extends beyond simple transcription; it serves as a vital tool for data analysis. Healthcare administrators can utilize coded data to identify trends in patient care, resource utilization, and treatment outcomes. This information allows them to make informed decisions on cost-effective practices without compromising quality care. For instance, identifying frequently performed procedures can lead to negotiations for better rates with suppliers or adjustments in staffing levels.


From a revenue growth perspective, precise medical coding maximizes reimbursements from payers by ensuring all services are captured accurately within claims submissions. It also supports strategic planning through detailed insights into service demand patterns and payer behaviors. As healthcare organizations strive to expand their offerings or enhance existing services, understanding these patterns becomes indispensable.


In addition to facilitating immediate financial transactions, accurate medical coding strengthens compliance with regulatory standards such as HIPAA (Health Insurance Portability and Accountability Act) in the United States. Adhering to these regulations not only avoids costly fines but also builds trust with patients and payers alike-a fundamental aspect of long-term revenue enhancement.


However, achieving this balance between cost control and revenue growth requires continuous investment in training skilled coders who stay current with evolving coding standards like ICD-10 (International Classification of Diseases). Technology also plays a significant role; advanced software solutions that automate parts of the coding process can increase efficiency while reducing human error.


In conclusion, medical coding is more than just an administrative function; it is a critical component that influences both sides of the financial equation in healthcare-cost control and revenue growth. By ensuring accuracy in billing processes and providing valuable data insights for strategic decision-making, medical coding helps sustain the economic vitality necessary for delivering high-quality patient care amidst ever-changing fiscal challenges.

In the intricate world of healthcare, medical coding operations serve as a vital conduit between clinical documentation and billing. As healthcare organizations strive to maintain financial health, they face the dual challenge of controlling costs while also fostering revenue growth. Successfully balancing these two objectives requires strategic approaches tailored to the unique landscape of medical coding.


Effective cost control in medical coding begins with optimizing staffing efficiency. This involves ensuring that coders are not only well-trained but also appropriately certified for their tasks. Investing in continuous education and providing access to advanced training can enhance accuracy and productivity, ultimately reducing costly errors and rework. Moreover, aligning staff levels with workload demands through data-driven scheduling can minimize overtime expenses and improve overall operational efficiency.


Another essential strategy is leveraging technology to streamline processes. Implementing sophisticated coding software equipped with artificial intelligence capabilities can significantly enhance accuracy and speed. These tools assist coders by auto-suggesting codes based on documentation, which reduces manual effort and error rates. Additionally, utilizing electronic health record (EHR) systems effectively ensures seamless integration of clinical documentation into the coding process, further enhancing efficiency.


Regular auditing and monitoring are also crucial for effective cost control. Conducting periodic audits helps identify areas where errors or inefficiencies may be occurring, allowing for timely corrections before they impact revenue flow adversely. By establishing robust internal controls and compliance checks, organizations can mitigate risks associated with inaccurate coding that often lead to denied claims or penalties.


Balancing cost control with revenue growth necessitates a focus on quality alongside quantity. High-quality coding not only ensures compliance but also maximizes reimbursements by capturing the full extent of services provided. Encouraging a culture of quality over quantity among coding professionals fosters meticulousness that directly contributes to accurate billing and optimal revenue capture.


Furthermore, fostering communication between departments such as finance, clinical staff, and coders is paramount in aligning goals towards both cost management and revenue enhancement. Regular cross-departmental meetings facilitate understanding each other's challenges and collaborating on solutions that benefit the organization holistically.


Lastly, staying abreast of industry changes-whether regulatory updates or shifts in reimbursement models-is imperative for both controlling costs and promoting revenue growth. Proactively adapting strategies in response to these changes positions an organization ahead of potential pitfalls while capitalizing on new opportunities.


In conclusion, navigating the complexities of medical coding operations requires a multifaceted approach focused on efficient staffing, technological integration, rigorous auditing practices, quality emphasis, interdepartmental collaboration, and adaptability to industry dynamics. By meticulously balancing these elements within their strategic framework, healthcare organizations can effectively control costs without compromising their potential for revenue growth-a delicate yet achievable equilibrium essential for long-term success in today's competitive healthcare environment.

Impact of Fee for Service on Medical Coding Practices

In today's rapidly evolving business landscape, the pursuit of growth often stands in a delicate balance with the imperative to control costs. As organizations strive to expand their market presence and increase revenue, they are simultaneously faced with the challenge of maintaining financial efficiency. One of the most effective strategies for achieving this equilibrium is leveraging technology and automation. By harnessing these tools, businesses can enhance operational efficiency while reducing costs, thereby fostering an environment where both cost control and revenue growth can thrive.


The integration of technology into business operations has revolutionized how companies function across various sectors. From streamlining supply chains to optimizing customer service, technological solutions enable firms to perform tasks with greater speed and precision than ever before. Automation, a subset of this technological advancement, further augments efficiency by handling repetitive processes that once required substantial human effort. Tasks such as data entry, inventory management, and even customer interactions through chatbots can now be automated, freeing up valuable human resources for more strategic initiatives.


One significant advantage of leveraging technology and automation is the reduction in operational costs. By automating routine tasks, businesses can minimize errors and reduce labor expenses associated with manual processes. This not only cuts down on direct costs but also mitigates potential losses from mistakes or inefficiencies. Moreover, technology solutions such as cloud computing allow companies to scale their IT infrastructure according to demand without incurring excessive expenditures on physical hardware.


Beyond cost savings, technology serves as a catalyst for revenue growth by enabling businesses to innovate and improve their offerings. Advanced data analytics provide insights into consumer behavior and market trends that inform strategic decision-making. With real-time information at their fingertips, companies can tailor products and services to meet evolving customer needs more effectively. This responsiveness not only enhances customer satisfaction but also positions firms competitively within their industries.


However, it is crucial for organizations to approach the adoption of technology with careful consideration. The initial investment in new technologies can be significant, necessitating a clear understanding of expected returns on investment (ROI). A strategic implementation plan ensures that technological upgrades align with overall business objectives without causing unnecessary disruption.


Moreover, while automation offers numerous benefits, it should complement rather than replace human expertise entirely. Businesses must strike a balance between automated functions and human oversight to maintain quality control and foster innovation-a domain where human creativity shines.


In conclusion, leveraging technology and automation presents an invaluable opportunity for businesses seeking to balance cost control with revenue growth. By enhancing operational efficiencies and reducing expenses through intelligent application of these tools, companies can create a sustainable path toward expansion without sacrificing financial stability. As they navigate this journey, organizations must remain mindful of aligning technological investments with broader strategic goals-ensuring that they not only keep pace with today's demands but also set themselves up for future success in an increasingly digital world.

Impact of Fee for Service on Medical Coding Practices

How Value Based Care Influences Medical Coding and Documentation Requirements

In the ever-evolving landscape of healthcare, medical coding stands as a critical pillar in bridging clinical care with financial stability. Ensuring accurate and compliant medical coding is not merely an operational necessity but a strategic imperative for maximizing revenue while maintaining cost control. As healthcare organizations strive to balance these two objectives-cost control and revenue growth-adhering to best practices in medical coding becomes paramount.


Medical coding involves translating complex clinical data into universally recognized codes that facilitate billing and reimbursement processes. It demands precision, a deep understanding of intricate guidelines, and constant vigilance to changes in regulations. The accuracy of this process directly influences the financial health of a healthcare organization, making it crucial for coders to be both meticulous and knowledgeable.


To begin with, comprehensive training programs are essential in equipping coders with the necessary skills and knowledge to handle the complexities of medical coding accurately. Regular workshops and certification updates ensure that coders remain abreast of changes in coding standards such as ICD-10, CPT, and HCPCS Level II codes. Coders who are well-trained can significantly reduce errors, prevent costly rejections or denials from payers, and ensure compliance with regulatory requirements.


Moreover, leveraging technology can greatly enhance the accuracy of medical coding. Advanced software solutions equipped with artificial intelligence can assist coders by flagging potential errors or suggesting appropriate codes based on documentation. These tools act as valuable allies in reducing human error while speeding up the coding process. However, technology should complement rather than replace human expertise; thus, continuous coder education remains vital.


Another fundamental practice is conducting regular audits and feedback sessions. Audits serve as an internal check mechanism to identify discrepancies or patterns indicative of systemic issues within the coding process. Constructive feedback helps refine coder skills further while also updating procedures that may contribute to inaccuracies. This iterative process fosters an environment focused on quality improvement-a cornerstone for cost control.


Effective communication between departments is also crucial for maintaining high standards in medical coding practices. Coders should work closely with clinical staff to ensure documentation is thorough and precise enough for accurate code assignment. Encouraging open lines of communication allows questions about ambiguous cases to be resolved swiftly, minimizing potential delays or errors in claim submissions.


Finally, emphasizing ethical practices cannot be overstated when it comes to compliant medical coding aimed at revenue maximization without sacrificing integrity or patient trust. Organizations must cultivate a culture where adherence to guidelines outweighs any temptation towards upcoding-a practice that might temporarily inflate revenues but poses significant legal risks.


In conclusion, achieving a balance between cost control and revenue growth through accurate and compliant medical coding requires a multifaceted approach rooted in education, technology integration, regular auditing, effective communication across departments, and unwavering commitment to ethical standards. By investing in these best practices consistently over time, healthcare organizations position themselves not only for immediate financial optimization but also sustainable success amidst an increasingly challenging economic climate.

Challenges and Benefits of Transitioning from Fee for Service to Value Based Care in Medical Coding

In the ever-evolving landscape of healthcare, medical coding stands as a pivotal component in bridging the gap between clinical services and financial outcomes. As healthcare providers continue to navigate the challenges of balancing cost control with revenue growth, analyzing data and trends becomes an indispensable strategy for identifying opportunities for revenue enhancement in medical coding.


Medical coding, the process of translating healthcare diagnoses, procedures, and services into universal codes, plays a crucial role in billing and reimbursement. However, beyond its fundamental purpose, it serves as a rich repository of data that can unlock insights into operational efficiency and financial performance. By meticulously analyzing this data, healthcare organizations can identify patterns and trends that may reveal untapped opportunities for revenue enhancement.


One key aspect of leveraging medical coding data is identifying areas where revenue leakage might occur. Inaccurate or incomplete coding not only hampers compliance but also results in significant financial losses. Through comprehensive audits and analyses, organizations can pinpoint discrepancies between provided services and coded information. This proactive approach allows them to rectify errors before they impact reimbursement rates negatively.


Additionally, trend analysis enables healthcare providers to anticipate shifts in service demand or changes in payer policies. For instance, if a particular procedure's frequency is increasing while reimbursement rates are declining, it may indicate a need to renegotiate contracts with insurers or adjust service offerings strategically. By staying ahead of these trends, providers can ensure they maintain a competitive edge while optimizing their revenue streams.


The integration of advanced analytics tools further empowers organizations to delve deeper into their coding data. Machine learning algorithms can sift through vast amounts of information to uncover hidden correlations between diagnoses and patient demographics or treatment outcomes. Such insights enable providers to tailor their services more effectively to meet patient needs while simultaneously enhancing profitability.


Moreover, fostering collaboration between clinical staff and coders is essential for maximizing revenue potential. Encouraging open communication ensures that coders have a clear understanding of the clinical nuances involved in patient care. This collaborative approach minimizes errors and fosters accurate documentation practices that align with reimbursement requirements.


Balancing cost control with revenue growth requires an intricate dance between efficiency and innovation. By harnessing the power of data analytics within medical coding processes, healthcare organizations can achieve both objectives harmoniously. They gain actionable insights that drive informed decision-making regarding resource allocation, service expansion, or strategic partnerships-all aimed at bolstering financial sustainability without compromising quality care delivery.


In conclusion, analyzing data and trends within medical coding offers healthcare organizations valuable opportunities for enhancing revenues while maintaining stringent control over costs. Through vigilant oversight coupled with technological advancements like machine learning algorithms or artificial intelligence-driven platforms-providers stand poised not only survive but thrive amidst ever-changing industry dynamics-ultimately achieving optimal outcomes both financially & clinically alike!

Case Studies Highlighting the Effects of Different Payment Models on Medical Coding Efficiency

In today's rapidly evolving business landscape, organizations constantly grapple with the dual challenges of maintaining cost control while fostering revenue growth. Amidst this balancing act, continuous education and training emerge as pivotal tools in ensuring quality and compliance, key drivers that underpin a company's long-term success.


Continuous education and training serve as the backbone for maintaining high standards of quality within an organization. By regularly updating employees on industry best practices, regulatory changes, and technological advancements, companies can ensure that their teams are equipped with the latest knowledge and skills. This proactive approach not only helps in mitigating risks associated with non-compliance but also enhances overall operational efficiency. When employees are well-versed in current standards and methodologies, they can perform their tasks more effectively, reducing errors and waste-factors that directly contribute to controlling costs.


Moreover, a commitment to ongoing learning fosters a culture of excellence within an organization. Employees who see that their personal development is valued are likely to be more engaged and motivated. This engagement translates into higher productivity levels, which ultimately supports revenue growth. A well-trained workforce is adept at identifying opportunities for innovation and improvement, enabling the organization to stay ahead of competitors by offering superior products or services.


Training programs also facilitate adaptability-a crucial trait for any business seeking to thrive in a dynamic market environment. As new technologies emerge and consumer preferences shift, companies must be nimble enough to pivot their strategies accordingly. Continuous education ensures that employees remain flexible and responsive to change, allowing the organization to harness new opportunities swiftly while maintaining compliance with ever-changing regulations.


In addition to enhancing internal capabilities, continuous learning initiatives signal a company's commitment to quality externally. Clients and partners value businesses that prioritize competence and compliance; thus, investing in employee development can strengthen relationships with stakeholders and enhance brand reputation-an intangible asset that contributes significantly to revenue growth.


However, it is important for organizations to implement these training programs strategically. Investing wisely in targeted education initiatives can yield substantial returns without unnecessary expenditure. Companies should conduct regular assessments to identify skill gaps within their workforce and tailor training solutions accordingly. Leveraging technology such as e-learning platforms can further optimize costs by delivering scalable training solutions across diverse geographical locations.


In conclusion, continuous education and training play a crucial role in balancing cost control with revenue growth by sustaining quality standards and ensuring compliance within an organization. By prioritizing employee development through strategic investment in learning initiatives, businesses not only enhance operational efficiency but also foster innovation and adaptability-key ingredients for thriving amidst competition while safeguarding profitability. Ultimately, this dedication positions organizations favorably for sustained success in today's ever-evolving marketplace.

Portrait of the Italian Luca Pacioli, painted by Jacopo de' Barbari, 1495, (Museo di Capodimonte). Pacioli is regarded as the Father of Accounting.

Bookkeeping is the recording of financial transactions, and is part of the process of accounting in business and other organizations.[1] It involves preparing source documents for all transactions, operations, and other events of a business. Transactions include purchases, sales, receipts and payments by an individual person, organization or corporation. There are several standard methods of bookkeeping, including the single-entry and double-entry bookkeeping systems. While these may be viewed as "real" bookkeeping, any process for recording financial transactions is a bookkeeping process.

The person in an organisation who is employed to perform bookkeeping functions is usually called the bookkeeper (or book-keeper). They usually write the daybooks (which contain records of sales, purchases, receipts, and payments), and document each financial transaction, whether cash or credit, into the correct daybook—that is, petty cash book, suppliers ledger, customer ledger, etc.—and the general ledger. Thereafter, an accountant can create financial reports from the information recorded by the bookkeeper. The bookkeeper brings the books to the trial balance stage, from which an accountant may prepare financial reports for the organisation, such as the income statement and balance sheet.

History

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The origin of book-keeping is lost in obscurity, but recent research indicates that methods of keeping accounts have existed from the remotest times of human life in cities. Babylonian records written with styli on small slabs of clay have been found dating to 2600 BC.[2] Mesopotamian bookkeepers kept records on clay tablets that may date back as far as 7,000 years. Use of the modern double entry bookkeeping system was described by Luca Pacioli in 1494.[3]

The term "waste book" was used in colonial America, referring to the documenting of daily transactions of receipts and expenditures. Records were made in chronological order, and for temporary use only. Daily records were then transferred to a daybook or account ledger to balance the accounts and to create a permanent journal; then the waste book could be discarded, hence the name.[4]

Process

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The primary purpose of bookkeeping is to record the financial effects of transactions. An important difference between a manual and an electronic accounting system is the former's latency between the recording of a financial transaction and its posting in the relevant account. This delay, which is absent in electronic accounting systems due to nearly instantaneous posting to relevant accounts, is characteristic of manual systems, and gave rise to the primary books of accounts—cash book, purchase book, sales book, etc.—for immediately documenting a financial transaction.

In the normal course of business, a document is produced each time a transaction occurs. Sales and purchases usually have invoices or receipts. Historically, deposit slips were produced when lodgements (deposits) were made to a bank account; and checks (spelled "cheques" in the UK and several other countries) were written to pay money out of the account. Nowadays such transactions are mostly made electronically. Bookkeeping first involves recording the details of all of these source documents into multi-column journals (also known as books of first entry or daybooks). For example, all credit sales are recorded in the sales journal; all cash payments are recorded in the cash payments journal. Each column in a journal normally corresponds to an account. In the single entry system, each transaction is recorded only once. Most individuals who balance their check-book each month are using such a system, and most personal-finance software follows this approach.

After a certain period, typically a month, each column in each journal is totalled to give a summary for that period. Using the rules of double-entry, these journal summaries are then transferred to their respective accounts in the ledger, or account book. For example, the entries in the Sales Journal are taken and a debit entry is made in each customer's account (showing that the customer now owes us money), and a credit entry might be made in the account for "Sale of class 2 widgets" (showing that this activity has generated revenue for us). This process of transferring summaries or individual transactions to the ledger is called posting. Once the posting process is complete, accounts kept using the "T" format (debits on the left side of the "T" and credits on the right side) undergo balancing, which is simply a process to arrive at the balance of the account.

As a partial check that the posting process was done correctly, a working document called an unadjusted trial balance is created. In its simplest form, this is a three-column list. Column One contains the names of those accounts in the ledger which have a non-zero balance. If an account has a debit balance, the balance amount is copied into Column Two (the debit column); if an account has a credit balance, the amount is copied into Column Three (the credit column). The debit column is then totalled, and then the credit column is totalled. The two totals must agree—which is not by chance—because under the double-entry rules, whenever there is a posting, the debits of the posting equal the credits of the posting. If the two totals do not agree, an error has been made, either in the journals or during the posting process. The error must be located and rectified, and the totals of the debit column and the credit column recalculated to check for agreement before any further processing can take place.

Once the accounts balance, the accountant makes a number of adjustments and changes the balance amounts of some of the accounts. These adjustments must still obey the double-entry rule: for example, the inventory account and asset account might be changed to bring them into line with the actual numbers counted during a stocktake. At the same time, the expense account associated with use of inventory is adjusted by an equal and opposite amount. Other adjustments such as posting depreciation and prepayments are also done at this time. This results in a listing called the adjusted trial balance. It is the accounts in this list, and their corresponding debit or credit balances, that are used to prepare the financial statements.

Finally financial statements are drawn from the trial balance, which may include:

Single-entry system

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The primary bookkeeping record in single-entry bookkeeping is the cash book, which is similar to a checking account register (in UK: cheque account, current account), except all entries are allocated among several categories of income and expense accounts. Separate account records are maintained for petty cash, accounts payable and accounts receivable, and other relevant transactions such as inventory and travel expenses. To save time and avoid the errors of manual calculations, single-entry bookkeeping can be done today with do-it-yourself bookkeeping software.

Double-entry system

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A double-entry bookkeeping system is a set of rules for recording financial information in a financial accounting system in which every transaction or event changes at least two different ledger accounts.

Daybooks

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A daybook is a descriptive and chronological (diary-like) record of day-to-day financial transactions; it is also called a book of original entry. The daybook's details must be transcribed formally into journals to enable posting to ledgers. Daybooks include:

  • Sales daybook, for recording sales invoices.
  • Sales credits daybook, for recording sales credit notes.
  • Purchases daybook, for recording purchase invoices.
  • Purchases debits daybook, for recording purchase debit notes.
  • Cash daybook, usually known as the cash book, for recording all monies received and all monies paid out. It may be split into two daybooks: a receipts daybook documenting every money-amount received, and a payments daybook recording every payment made.
  • General Journal daybook, for recording journal entries.

Petty cash book

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A petty cash book is a record of small-value purchases before they are later transferred to the ledger and final accounts; it is maintained by a petty or junior cashier. This type of cash book usually uses the imprest system: a certain amount of money is provided to the petty cashier by the senior cashier. This money is to cater for minor expenditures (hospitality, minor stationery, casual postage, and so on) and is reimbursed periodically on satisfactory explanation of how it was spent. The balance of petty cash book is Asset.

Journals

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Journals are recorded in the general journal daybook. A journal is a formal and chronological record of financial transactions before their values are accounted for in the general ledger as debits and credits. A company can maintain one journal for all transactions, or keep several journals based on similar activity (e.g., sales, cash receipts, revenue, etc.), making transactions easier to summarize and reference later. For every debit journal entry recorded, there must be an equivalent credit journal entry to maintain a balanced accounting equation.[5][6]

Ledgers

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A ledger is a record of accounts. The ledger is a permanent summary of all amounts entered in supporting Journals which list individual transactions by date. These accounts are recorded separately, showing their beginning/ending balance. A journal lists financial transactions in chronological order, without showing their balance but showing how much is going to be entered in each account. A ledger takes each financial transaction from the journal and records it into the corresponding accounts. The ledger also determines the balance of every account, which is transferred into the balance sheet or the income statement. There are three different kinds of ledgers that deal with book-keeping:

  • Sales ledger, which deals mostly with the accounts receivable account. This ledger consists of the records of the financial transactions made by customers to the business.
  • Purchase ledger is the record of the company's purchasing transactions; it goes hand in hand with the Accounts Payable account.
  • General ledger, representing the original five, main accounts: assets, liabilities, equity, income, and expenses.

Abbreviations used in bookkeeping

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  • A/c or Acc – Account
  • A/R – Accounts receivable
  • A/P – Accounts payable
  • B/S – Balance sheet
  • c/d – Carried down
  • b/d – Brought down
  • c/f – Carried forward
  • b/f – Brought forward
  • Dr – Debit side of a ledger. "Dr" stands for "Debit register"
  • Cr – Credit side of a ledger. "Cr" stands for "Credit register"
  • G/L – General ledger; (or N/L – nominal ledger)
  • PL – Profit and loss; (or I/S – income statement)
  • P/L – Purchase Ledger (Accounts payable)
  • P/R – Payroll
  • PP&E – Property, plant and equipment
  • S/L - Sales Ledger (Accounts receivable)
  • TB – Trial Balance
  • GST – Goods and services tax
  • SGST – State goods & service tax
  • CGST – Central goods & service tax
  • IGST- integrated goods & service tax
  • VAT – Value added tax
  • CST – Central sale tax
  • TDS – Tax deducted at source
  • AMT – Alternate minimum tax
  • EBT – Earnings before tax
  • EAT – Earnings after tax
  • PAT – Profit after tax
  • PBT – Profit before tax
  • Dep or Depr – Depreciation
  • CPO – Cash paid out
  • CP - Cash Payment
  • w.e.f. - with effect from
  • @ - at the rate of
  • L/F – ledger folio
  • J/F – Journal Folio
  • M/s- Messrs Account
  • Co- Company
  • V/N or V.no. – voucher number
  • In no -invoice Number

Chart of accounts

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A chart of accounts is a list of the accounts codes that can be identified with numeric, alphabetical, or alphanumeric codes allowing the account to be located in the general ledger. The equity section of the chart of accounts is based on the fact that the legal structure of the entity is of a particular legal type. Possibilities include sole trader, partnership, trust, and company.[7]

Computerized bookkeeping

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Computerized bookkeeping removes many of the paper "books" that are used to record the financial transactions of a business entity; instead, relational databases are used today, but typically, these still enforce the norms of bookkeeping including the single-entry and double-entry bookkeeping systems. Certified Public Accountants (CPAs) supervise the internal controls for computerized bookkeeping systems, which serve to minimize errors in documenting the numerous activities a business entity may initiate or complete over an accounting period.

See also

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References

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  1. ^ Weygandt; Kieso; Kimmel (2003). Financial Accounting. Susan Elbe. p. 6. ISBN 0-471-07241-9.
  2. ^ Chisholm, Hugh, ed. (1911). "Book-Keeping" . Encyclopædia Britannica. Vol. 4 (11th ed.). Cambridge University Press. p. 225.
  3. ^ "History of Accounting". Fremont University. Retrieved 2022-07-15.
  4. ^ "Pittsburgh Waste Book and Fort Pitt Trading Post Papers". Guides to Archives and Manuscript Collections at the University of Pittsburgh Library System. Retrieved 2015-09-04.
  5. ^ Haber, Jeffry (2004). Accounting Demystified. New York: AMACOM. p. 15. ISBN 0-8144-0790-0.
  6. ^ Raza, SyedA. Accountants Information. p. Accountant in Milton Keynes.
  7. ^ Marsden,Stephen (2008). Australian Master Bookkeepers Guide. Sydney: CCH ISBN 978-1-921593-57-4
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American students learning how to make and roll sushi

Learning is the process of acquiring new understanding, knowledge, behaviors, skills, values, attitudes, and preferences.[1] The ability to learn is possessed by humans, non-human animals, and some machines; there is also evidence for some kind of learning in certain plants.[2] Some learning is immediate, induced by a single event (e.g. being burned by a hot stove), but much skill and knowledge accumulate from repeated experiences.[3] The changes induced by learning often last a lifetime, and it is hard to distinguish learned material that seems to be "lost" from that which cannot be retrieved.[4]

Human learning starts at birth (it might even start before[5]) and continues until death as a consequence of ongoing interactions between people and their environment. The nature and processes involved in learning are studied in many established fields (including educational psychology, neuropsychology, experimental psychology, cognitive sciences, and pedagogy), as well as emerging fields of knowledge (e.g. with a shared interest in the topic of learning from safety events such as incidents/accidents,[6] or in collaborative learning health systems[7]). Research in such fields has led to the identification of various sorts of learning. For example, learning may occur as a result of habituation, or classical conditioning, operant conditioning or as a result of more complex activities such as play, seen only in relatively intelligent animals.[8][9] Learning may occur consciously or without conscious awareness. Learning that an aversive event cannot be avoided or escaped may result in a condition called learned helplessness.[10] There is evidence for human behavioral learning prenatally, in which habituation has been observed as early as 32 weeks into gestation, indicating that the central nervous system is sufficiently developed and primed for learning and memory to occur very early on in development.[11]

Play has been approached by several theorists as a form of learning. Children experiment with the world, learn the rules, and learn to interact through play. Lev Vygotsky agrees that play is pivotal for children's development, since they make meaning of their environment through playing educational games. For Vygotsky, however, play is the first form of learning language and communication, and the stage where a child begins to understand rules and symbols.[12] This has led to a view that learning in organisms is always related to semiosis,[13] and is often associated with representational systems/activity.[14]

Types

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There are various functional categorizations of memory which have developed. Some memory researchers distinguish memory based on the relationship between the stimuli involved (associative vs non-associative) or based to whether the content can be communicated through language (declarative/explicit vs procedural/implicit). Some of these categories can, in turn, be parsed into sub-types. For instance, declarative memory comprises both episodic and semantic memory.

Children learn to bike in the eighties in Czechoslovakia.

Non-associative learning

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Non-associative learning refers to "a relatively permanent change in the strength of response to a single stimulus due to repeated exposure to that stimulus."[15] This definition exempts the changes caused by sensory adaptation, fatigue, or injury.[16]

Non-associative learning can be divided into habituation and sensitization.

Habituation

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Habituation is an example of non-associative learning in which one or more components of an innate response (e.g., response probability, response duration) to a stimulus diminishes when the stimulus is repeated. Thus, habituation must be distinguished from extinction, which is an associative process. In operant extinction, for example, a response declines because it is no longer followed by a reward. An example of habituation can be seen in small song birds—if a stuffed owl (or similar predator) is put into the cage, the birds initially react to it as though it were a real predator. Soon the birds react less, showing habituation. If another stuffed owl is introduced (or the same one removed and re-introduced), the birds react to it again as though it were a predator, demonstrating that it is only a very specific stimulus that is habituated to (namely, one particular unmoving owl in one place). The habituation process is faster for stimuli that occur at a high rather than for stimuli that occur at a low rate as well as for the weak and strong stimuli, respectively.[17] Habituation has been shown in essentially every species of animal, as well as the sensitive plant Mimosa pudica[18] and the large protozoan Stentor coeruleus.[19] This concept acts in direct opposition to sensitization.[17]

Sensitization

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Sensitization is an example of non-associative learning in which the progressive amplification of a response follows repeated administrations of a stimulus.[20] This is based on the notion that a defensive reflex to a stimulus such as withdrawal or escape becomes stronger after the exposure to a different harmful or threatening stimulus.[21] An everyday example of this mechanism is the repeated tonic stimulation of peripheral nerves that occurs if a person rubs their arm continuously. After a while, this stimulation creates a warm sensation that can eventually turn painful. This pain results from a progressively amplified synaptic response of the peripheral nerves. This sends a warning that the stimulation is harmful.[22][clarification needed] Sensitization is thought to underlie both adaptive as well as maladaptive learning processes in the organism.[23][citation needed]

Active learning

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Active learning occurs when a person takes control of his/her learning experience. Since understanding information is the key aspect of learning, it is important for learners to recognize what they understand and what they do not. By doing so, they can monitor their own mastery of subjects. Active learning encourages learners to have an internal dialogue in which they verbalize understandings. This and other meta-cognitive strategies can be taught to a child over time. Studies within metacognition have proven the value in active learning, claiming that the learning is usually at a stronger level as a result.[24] In addition, learners have more incentive to learn when they have control over not only how they learn but also what they learn.[25] Active learning is a key characteristic of student-centered learning. Conversely, passive learning and direct instruction are characteristics of teacher-centered learning (or traditional education).

Associative learning

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Associative learning is the process by which a person or animal learns an association between two stimuli or events.[26] In classical conditioning, a previously neutral stimulus is repeatedly paired with a reflex-eliciting stimulus until eventually the neutral stimulus elicits a response on its own. In operant conditioning, a behavior that is reinforced or punished in the presence of a stimulus becomes more or less likely to occur in the presence of that stimulus.

Operant conditioning

[edit]

Operant conditioning is a way in which behavior can be shaped or modified according to the desires of the trainer or head individual. Operant conditioning uses the thought that living things seek pleasure and avoid pain, and that an animal or human can learn through receiving either reward or punishment at a specific time called trace conditioning. Trace conditioning is the small and ideal period of time between the subject performing the desired behavior, and receiving the positive reinforcement as a result of their performance. The reward needs to be given immediately after the completion of the wanted behavior.[27]

Operant conditioning is different from classical conditioning in that it shapes behavior not solely on bodily reflexes that occur naturally to a specific stimulus, but rather focuses on the shaping of wanted behavior that requires conscious thought, and ultimately requires learning.[28]

Punishment and reinforcement are the two principal ways in which operant conditioning occurs. Punishment is used to reduce unwanted behavior, and ultimately (from the learner's perspective) leads to avoidance of the punishment, not necessarily avoidance of the unwanted behavior. Punishment is not an appropriate way to increase wanted behavior for animals or humans. Punishment can be divided into two subcategories, positive punishment and negative punishment. Positive punishment is when an aversive aspect of life or thing is added to the subject, for this reason it is called positive punishment. For example, the parent spanking their child would be considered a positive punishment, because a spanking was added to the child. Negative punishment is considered the removal of something loved or desirable from the subject. For example, when a parent puts his child in time out, in reality, the child is losing the opportunity to be with friends, or to enjoy the freedom to do as he pleases. In this example, negative punishment is the removal of the child's desired rights to play with his friends etc.[29][30]

Reinforcement on the other hand is used to increase a wanted behavior either through negative reinforcement or positive reinforcement. Negative reinforcement is defined by removing an undesirable aspect of life, or thing. For example, a dog might learn to sit as the trainer scratches his ears, which ultimately is removing his itches (undesirable aspect). Positive reinforcement is defined by adding a desirable aspect of life or thing. For example, a dog might learn to sit if he receives a treat. In this example the treat was added to the dog's life.[29][30]

Classical conditioning

[edit]

The typical paradigm for classical conditioning involves repeatedly pairing an unconditioned stimulus (which unfailingly evokes a reflexive response) with another previously neutral stimulus (which does not normally evoke the response). Following conditioning, the response occurs both to the unconditioned stimulus and to the other, unrelated stimulus (now referred to as the "conditioned stimulus"). The response to the conditioned stimulus is termed a conditioned response. The classic example is Ivan Pavlov and his dogs.[21] Pavlov fed his dogs meat powder, which naturally made the dogs salivate—salivating is a reflexive response to the meat powder. Meat powder is the unconditioned stimulus (US) and the salivation is the unconditioned response (UR). Pavlov rang a bell before presenting the meat powder. The first time Pavlov rang the bell, the neutral stimulus, the dogs did not salivate, but once he put the meat powder in their mouths they began to salivate. After numerous pairings of bell and food, the dogs learned that the bell signaled that food was about to come, and began to salivate when they heard the bell. Once this occurred, the bell became the conditioned stimulus (CS) and the salivation to the bell became the conditioned response (CR). Classical conditioning has been demonstrated in many species. For example, it is seen in honeybees, in the proboscis extension reflex paradigm.[31] It was recently also demonstrated in garden pea plants.[32]

Another influential person in the world of classical conditioning is John B. Watson. Watson's work was very influential and paved the way for B.F. Skinner's radical behaviorism. Watson's behaviorism (and philosophy of science) stood in direct contrast to Freud and other accounts based largely on introspection. Watson's view was that the introspective method was too subjective and that we should limit the study of human development to directly observable behaviors. In 1913, Watson published the article "Psychology as the Behaviorist Views", in which he argued that laboratory studies should serve psychology best as a science. Watson's most famous, and controversial, experiment was "Little Albert", where he demonstrated how psychologists can account for the learning of emotion through classical conditioning principles.

Observational learning

[edit]

Observational learning is learning that occurs through observing the behavior of others. It is a form of social learning which takes various forms, based on various processes. In humans, this form of learning seems to not need reinforcement to occur, but instead, requires a social model such as a parent, sibling, friend, or teacher with surroundings.

Imprinting

[edit]

Imprinting is a kind of learning occurring at a particular life stage that is rapid and apparently independent of the consequences of behavior. In filial imprinting, young animals, particularly birds, form an association with another individual or in some cases, an object, that they respond to as they would to a parent. In 1935, the Austrian Zoologist Konrad Lorenz discovered that certain birds follow and form a bond if the object makes sounds.

Play

[edit]

Play generally describes behavior with no particular end in itself, but that improves performance in similar future situations. This is seen in a wide variety of vertebrates besides humans, but is mostly limited to mammals and birds. Cats are known to play with a ball of string when young, which gives them experience with catching prey. Besides inanimate objects, animals may play with other members of their own species or other animals, such as orcas playing with seals they have caught. Play involves a significant cost to animals, such as increased vulnerability to predators and the risk of injury and possibly infection. It also consumes energy, so there must be significant benefits associated with play for it to have evolved. Play is generally seen in younger animals, suggesting a link with learning. However, it may also have other benefits not associated directly with learning, for example improving physical fitness.

Play, as it pertains to humans as a form of learning is central to a child's learning and development. Through play, children learn social skills such as sharing and collaboration. Children develop emotional skills such as learning to deal with the emotion of anger, through play activities. As a form of learning, play also facilitates the development of thinking and language skills in children.[33]

There are five types of play:

  1. Sensorimotor play aka functional play, characterized by the repetition of an activity
  2. Roleplay occurs starting at the age of three
  3. Rule-based play where authoritative prescribed codes of conduct are primary
  4. Construction play involves experimentation and building
  5. Movement play aka physical play[33]

These five types of play are often intersecting. All types of play generate thinking and problem-solving skills in children. Children learn to think creatively when they learn through play.[34] Specific activities involved in each type of play change over time as humans progress through the lifespan. Play as a form of learning, can occur solitarily, or involve interacting with others.

Enculturation

[edit]

Enculturation is the process by which people learn values and behaviors that are appropriate or necessary in their surrounding culture.[35] Parents, other adults, and peers shape the individual's understanding of these values.[35] If successful, enculturation results in competence in the language, values, and rituals of the culture.[35] This is different from acculturation, where a person adopts the values and societal rules of a culture different from their native one.

Multiple examples of enculturation can be found cross-culturally. Collaborative practices in the Mazahua people have shown that participation in everyday interaction and later learning activities contributed to enculturation rooted in nonverbal social experience.[36] As the children participated in everyday activities, they learned the cultural significance of these interactions. The collaborative and helpful behaviors exhibited by Mexican and Mexican-heritage children is a cultural practice known as being "acomedido".[37] Chillihuani girls in Peru described themselves as weaving constantly, following behavior shown by the other adults.[38]

Episodic learning

[edit]

Episodic learning is a change in behavior that occurs as a result of an event.[39] For example, a fear of dogs that follows being bitten by a dog is episodic learning. Episodic learning is so named because events are recorded into episodic memory, which is one of the three forms of explicit learning and retrieval, along with perceptual memory and semantic memory.[40] Episodic memory remembers events and history that are embedded in experience and this is distinguished from semantic memory, which attempts to extract facts out of their experiential context[41] or – as some describe – a timeless organization of knowledge.[42] For instance, if a person remembers the Grand Canyon from a recent visit, it is an episodic memory. He would use semantic memory to answer someone who would ask him information such as where the Grand Canyon is. A study revealed that humans are very accurate in the recognition of episodic memory even without deliberate intention to memorize it.[43] This is said to indicate a very large storage capacity of the brain for things that people pay attention to.[43]

Multimedia learning

[edit]

Multimedia learning is where a person uses both auditory and visual stimuli to learn information.[44] This type of learning relies on dual-coding theory.[45]

E-learning and augmented learning

[edit]

Electronic learning or e-learning is computer-enhanced learning. A specific and always more diffused e-learning is mobile learning (m-learning), which uses different mobile telecommunication equipment, such as cellular phones.

When a learner interacts with the e-learning environment, it is called augmented learning. By adapting to the needs of individuals, the context-driven instruction can be dynamically tailored to the learner's natural environment. Augmented digital content may include text, images, video, audio (music and voice). By personalizing instruction, augmented learning has been shown to improve learning performance for a lifetime.[46] See also minimally invasive education.

Moore (1989)[47] purported that three core types of interaction are necessary for quality, effective online learning:

  • Learner–learner (i.e. communication between and among peers with or without the teacher present),
  • Learner–instructor (i.e. student-teacher communication), and
  • Learner–content (i.e. intellectually interacting with content that results in changes in learners' understanding, perceptions, and cognitive structures).

In his theory of transactional distance, Moore (1993)[48] contented that structure and interaction or dialogue bridge the gap in understanding and communication that is created by geographical distances (known as transactional distance).

Rote learning

[edit]

Rote learning is memorizing information so that it can be recalled by the learner exactly the way it was read or heard. The major technique used for rote learning is learning by repetition, based on the idea that a learner can recall the material exactly (but not its meaning) if the information is repeatedly processed. Rote learning is used in diverse areas, from mathematics to music to religion.

Meaningful learning

[edit]

Meaningful learning is the concept that learned knowledge (e.g., a fact) is fully understood to the extent that it relates to other knowledge. To this end, meaningful learning contrasts with rote learning in which information is acquired without regard to understanding. Meaningful learning, on the other hand, implies there is a comprehensive knowledge of the context of the facts learned.[49]

Evidence-based learning

[edit]

Evidence-based learning is the use of evidence from well designed scientific studies to accelerate learning. Evidence-based learning methods such as spaced repetition can increase the rate at which a student learns.[50]

Formal learning

[edit]
A depiction of the world's oldest continually operating university, the University of Bologna, Italy

Formal learning is a deliberate way attaining of knowledge, which takes place within a teacher-student environment, such as in a school system or work environment.[51][52] The term formal learning has nothing to do with the formality of the learning, but rather the way it is directed and organized. In formal learning, the learning or training departments set out the goals and objectives of the learning and oftentimes learners will be awarded with a diploma, or a type of formal recognition.[51][53]

Non-formal learning

[edit]

Non-formal learning is organized learning outside the formal learning system. For example, learning by coming together with people with similar interests and exchanging viewpoints, in clubs or in (international) youth organizations, and workshops. From the organizer's point of reference, non-formal learning does not always need a main objective or learning outcome. From the learner's point of view, non-formal learning, although not focused on outcomes, often results in an intentional learning opportunity.[54]

Informal learning

[edit]

Informal learning is less structured than "non-formal learning". It may occur through the experience of day-to-day situations (for example, one would learn to look ahead while walking because of the possible dangers inherent in not paying attention to where one is going). It is learning from life, during a meal at the table with parents, during play, and while exploring etc.. For the learner, informal learning is most often an experience of happenstance, and not a deliberately planned experience. Thus this does not require enrollment into any class. Unlike formal learning, informal learning typically does not lead to accreditation.[54] Informal learning begins to unfold as the learner ponders his or her situation. This type of learning does not require a professor of any kind, and learning outcomes are unforeseen following the learning experience.[55]

Informal learning is self-directed and because it focuses on day-to-day situations, the value of informal learning can be considered high. As a result, information retrieved from informal learning experiences will likely be applicable to daily life.[56] Children with informal learning can at times yield stronger support than subjects with formal learning in the topic of mathematics.[57] Daily life experiences take place in the workforce, family life, and any other situation that may arise during one's lifetime. Informal learning is voluntary from the learner's viewpoint, and may require making mistakes and learning from them. Informal learning allows the individual to discover coping strategies for difficult emotions that may arise while learning. From the learner's perspective, informal learning can become purposeful, because the learner chooses which rate is appropriate to learn and because this type of learning tends to take place within smaller groups or by oneself.[56]

Nonformal learning and combined approaches

[edit]

The educational system may use a combination of formal, informal, and nonformal learning methods. The UN and EU recognize these different forms of learning (cf. links below). In some schools, students can get points that count in the formal-learning systems if they get work done in informal-learning circuits. They may be given time to assist international youth workshops and training courses, on the condition they prepare, contribute, share, and can prove this offered valuable new insight, helped to acquire new skills, a place to get experience in organizing, teaching, etc.

To learn a skill, such as solving a Rubik's Cube quickly, several factors come into play at once:

  • Reading directions helps a player learn the patterns that solve the Rubik's Cube.
  • Practicing the moves repeatedly helps build "muscle memory" and speed.
  • Thinking critically about moves helps find shortcuts, which speeds future attempts.
  • Observing the Rubik's Cube's six colors help anchor solutions in the mind.
  • Revisiting the cube occasionally helps retain the skill.

Tangential learning

[edit]

Tangential learning is the process by which people self-educate if a topic is exposed to them in a context that they already enjoy. For example, after playing a music-based video game, some people may be motivated to learn how to play a real instrument, or after watching a TV show that references Faust and Lovecraft, some people may be inspired to read the original work.[58] Self-education can be improved with systematization. According to experts in natural learning, self-oriented learning training has proven an effective tool for assisting independent learners with the natural phases of learning.[59]

Extra Credits writer and game designer James Portnow was the first to suggest games as a potential venue for "tangential learning".[60] Mozelius et al.[61] points out that intrinsic integration of learning content seems to be a crucial design factor, and that games that include modules for further self-studies tend to present good results. The built-in encyclopedias in the Civilization games are presented as an example – by using these modules gamers can dig deeper for knowledge about historical events in the gameplay. The importance of rules that regulate learning modules and game experience is discussed by Moreno, C.,[62] in a case study about the mobile game Kiwaka. In this game, developed by Landka in collaboration with ESA and ESO, progress is rewarded with educational content, as opposed to traditional education games where learning activities are rewarded with gameplay.[63][64]

Dialogic learning

[edit]

Dialogic learning is a type of learning based on dialogue.

Incidental learning

[edit]

In incidental teaching learning is not planned by the instructor or the student, it occurs as a byproduct of another activity — an experience, observation, self-reflection, interaction, unique event (e.g. in response to incidents/accidents), or common routine task. This learning happens in addition to or apart from the instructor's plans and the student's expectations. An example of incidental teaching is when the instructor places a train set on top of a cabinet. If the child points or walks towards the cabinet, the instructor prompts the student to say "train". Once the student says "train", he gets access to the train set.

Here are some steps most commonly used in incidental teaching:[65]

  • An instructor will arrange the learning environment so that necessary materials are within the student's sight, but not within his reach, thus impacting his motivation to seek out those materials.
  • An instructor waits for the student to initiate engagement.
  • An instructor prompts the student to respond if needed.
  • An instructor allows access to an item/activity contingent on a correct response from the student.
  • The instructor fades out the prompting process over a period of time and subsequent trials.

Incidental learning is an occurrence that is not generally accounted for using the traditional methods of instructional objectives and outcomes assessment. This type of learning occurs in part as a product of social interaction and active involvement in both online and onsite courses. Research implies that some un-assessed aspects of onsite and online learning challenge the equivalency of education between the two modalities. Both onsite and online learning have distinct advantages with traditional on-campus students experiencing higher degrees of incidental learning in three times as many areas as online students. Additional research is called for to investigate the implications of these findings both conceptually and pedagogically.[66]

Domains

[edit]
Future school (1901 or 1910)

Benjamin Bloom has suggested three domains of learning in his taxonomy which are:

  • Cognitive: To recall, calculate, discuss, analyze, problem solve, etc.
  • Psychomotor: To dance, swim, ski, dive, drive a car, ride a bike, etc.
  • Affective: To like something or someone, love, appreciate, fear, hate, worship, etc.

These domains are not mutually exclusive. For example, in learning to play chess, the person must learn the rules (cognitive domain)—but must also learn how to set up the chess pieces and how to properly hold and move a chess piece (psychomotor). Furthermore, later in the game the person may even learn to love the game itself, value its applications in life, and appreciate its history (affective domain).[67]

Transfer

[edit]

Transfer of learning is the application of skill, knowledge or understanding to resolve a novel problem or situation that happens when certain conditions are fulfilled. Research indicates that learning transfer is infrequent; most common when "... cued, primed, and guided..."[68] and has sought to clarify what it is, and how it might be promoted through instruction.

Over the history of its discourse, various hypotheses and definitions have been advanced. First, it is speculated that different types of transfer exist, including: near transfer, the application of skill to solve a novel problem in a similar context; and far transfer, the application of skill to solve a novel problem presented in a different context.[69] Furthermore, Perkins and Salomon (1992) suggest that positive transfer in cases when learning supports novel problem solving, and negative transfer occurs when prior learning inhibits performance on highly correlated tasks, such as second or third-language learning.[70] Concepts of positive and negative transfer have a long history; researchers in the early 20th century described the possibility that "...habits or mental acts developed by a particular kind of training may inhibit rather than facilitate other mental activities".[71] Finally, Schwarz, Bransford and Sears (2005) have proposed that transferring knowledge into a situation may differ from transferring knowledge out to a situation as a means to reconcile findings that transfer may both be frequent and challenging to promote.[72]

A significant and long research history has also attempted to explicate the conditions under which transfer of learning might occur. Early research by Ruger, for example, found that the "level of attention", "attitudes", "method of attack" (or method for tackling a problem), a "search for new points of view", a "careful testing of hypothesis" and "generalization" were all valuable approaches for promoting transfer.[73] To encourage transfer through teaching, Perkins and Salomon recommend aligning ("hugging") instruction with practice and assessment, and "bridging", or encouraging learners to reflect on past experiences or make connections between prior knowledge and current content.[70]

Factors affecting learning

[edit]

Genetics

[edit]

Some aspects of intelligence are inherited genetically, so different learners to some degree have different abilities with regard to learning and speed of learning.[citation needed]

Socioeconomic and physical conditions

[edit]

Problems like malnutrition, fatigue, and poor physical health can slow learning, as can bad ventilation or poor lighting at home, and unhygienic living conditions.[74][75]

The design, quality, and setting of a learning space, such as a school or classroom, can each be critical to the success of a learning environment. Size, configuration, comfort—fresh air, temperature, light, acoustics, furniture—can all affect a student's learning. The tools used by both instructors and students directly affect how information is conveyed, from the display and writing surfaces (blackboards, markerboards, tack surfaces) to digital technologies. For example, if a room is too crowded, stress levels rise, student attention is reduced, and furniture arrangement is restricted. If furniture is incorrectly arranged, sightlines to the instructor or instructional material are limited and the ability to suit the learning or lesson style is restricted. Aesthetics can also play a role, for if student morale suffers, so does motivation to attend school.[76][77]

Psychological factors and teaching style

[edit]

Intrinsic motivation, such as a student's own intellectual curiosity or desire to experiment or explore, has been found to sustain learning more effectively than extrinsic motivations such as grades or parental requirements. Rote learning involves repetition in order to reinforce facts in memory, but has been criticized as ineffective and "drill and kill" since it kills intrinsic motivation. Alternatives to rote learning include active learning and meaningful learning.

The speed, accuracy, and retention, depend upon aptitude, attitude, interest, attention, energy level, and motivation of the students. Students who answer a question properly or give good results should be praised. This encouragement increases their ability and helps them produce better results. Certain attitudes, such as always finding fault in a student's answer or provoking or embarrassing the student in front of a class are counterproductive.[78][79][need quotation to verify]

Certain techniques can increase long-term retention:[80]

  • The spacing effect means that lessons or studying spaced out over time (spaced repetition) are better than cramming
  • Teaching material to other people
  • "Self-explaining" (paraphrasing material to oneself) rather than passive reading
  • Low-stakes quizzing

Epigenetic factors

[edit]

The underlying molecular basis of learning appears to be dynamic changes in gene expression occurring in brain neurons that are introduced by epigenetic mechanisms. Epigenetic regulation of gene expression involves, most notably, chemical modification of DNA or DNA-associated histone proteins. These chemical modifications can cause long-lasting changes in gene expression. Epigenetic mechanisms involved in learning include the methylation and demethylation of neuronal DNA as well as methylation, acetylation and deacetylation of neuronal histone proteins.

During learning, information processing in the brain involves induction of oxidative modification in neuronal DNA followed by the employment of DNA repair processes that introduce epigenetic alterations. In particular, the DNA repair processes of non-homologous end joining and base excision repair are employed in learning and memory formation.[81][82]

[edit]

The nervous system continues to develop during adulthood until brain death. For example:

  • physical exercise has neurobiological effects
  • the consumption of foods (or nutrients), obesity,[83] alterations of the microbiome, drinks, dietary supplements, recreational drugs and medications[84][85] may possibly also have effects on the development of the nervous system
  • various diseases, such as COVID-19, have effects on the development of the nervous system
    • For example, several genes have been identified as being associated with changes in brain structure over lifetime and are potential Alzheimer's disease therapy-targets.[86][87]
  • psychological events such as mental trauma and resilience-building
  • exposure to environmental pollution and toxins such as air pollution may have effects on the further development of the nervous system
  • other activities may also have effects on the development of the nervous system, such as lifelong learning, retraining, and types of media- and economic activities
  • broadly, brain aging

Adult learning vs children's learning

[edit]

Learning is often more efficient in children and takes longer or is more difficult with age. A study using neuroimaging identified rapid neurotransmitter GABA boosting as a major potential explanation-component for why that is.[88][89]

Children's brains contain more "silent synapses" that are inactive until recruited as part of neuroplasticity and flexible learning or memories.[90][91] Neuroplasticity is heightened during critical or sensitive periods of brain development, mainly referring to brain development during child development.[92]

However researchers, after subjecting late middle aged participants to university courses, suggest perceived age differences in learning may be a result of differences in time, support, environment, and attitudes, rather than inherent ability.[93]

What humans learn at the early stages, and what they learn to apply, sets humans on course for life or has a disproportional impact.[94] Adults usually have a higher capacity to select what they learn, to what extent and how. For example, children may learn the given subjects and topics of school curricula via classroom blackboard-transcription handwriting, instead of being able to choose specific topics/skills or jobs to learn and the styles of learning. For instance, children may not have developed consolidated interests, ethics, interest in purpose and meaningful activities, knowledge about real-world requirements and demands, and priorities.

In animal evolution

[edit]

Animals gain knowledge in two ways. First is learning—in which an animal gathers information about its environment and uses this information. For example, if an animal eats something that hurts its stomach, it learns not to eat that again. The second is innate knowledge that is genetically inherited. An example of this is when a horse is born and can immediately walk. The horse has not learned this behavior; it simply knows how to do it.[95] In some scenarios, innate knowledge is more beneficial than learned knowledge. However, in other scenarios the opposite is true—animals must learn certain behaviors when it is disadvantageous to have a specific innate behavior. In these situations, learning evolves in the species.

Costs and benefits of learned and innate knowledge

[edit]

In a changing environment, an animal must constantly gain new information to survive. However, in a stable environment, this same individual needs to gather the information it needs once, and then rely on it for the rest of its life. Therefore, different scenarios better suit either learning or innate knowledge. Essentially, the cost of obtaining certain knowledge versus the benefit of already having it determines whether an animal evolved to learn in a given situation, or whether it innately knew the information. If the cost of gaining the knowledge outweighs the benefit of having it, then the animal does not evolve to learn in this scenario—but instead, non-learning evolves. However, if the benefit of having certain information outweighs the cost of obtaining it, then the animal is far more likely to evolve to have to learn this information.[95]

Non-learning is more likely to evolve in two scenarios. If an environment is static and change does not or rarely occurs, then learning is simply unnecessary. Because there is no need for learning in this scenario—and because learning could prove disadvantageous due to the time it took to learn the information—non-learning evolves. Similarly, if an environment is in a constant state of change, learning is also disadvantageous, as anything learned is immediately irrelevant because of the changing environment.[95] The learned information no longer applies. Essentially, the animal would be just as successful if it took a guess as if it learned. In this situation, non-learning evolves. In fact, a study of Drosophila melanogaster showed that learning can actually lead to a decrease in productivity, possibly because egg-laying behaviors and decisions were impaired by interference from the memories gained from the newly learned materials or because of the cost of energy in learning.[96]

However, in environments where change occurs within an animal's lifetime but is not constant, learning is more likely to evolve. Learning is beneficial in these scenarios because an animal can adapt to the new situation, but can still apply the knowledge that it learns for a somewhat extended period of time. Therefore, learning increases the chances of success as opposed to guessing.[95] An example of this is seen in aquatic environments with landscapes subject to change. In these environments, learning is favored because the fish are predisposed to learn the specific spatial cues where they live.[97]

In plants

[edit]

In recent years, plant physiologists have examined the physiology of plant behavior and cognition. The concepts of learning and memory are relevant in identifying how plants respond to external cues, a behavior necessary for survival. Monica Gagliano, an Australian professor of evolutionary ecology, makes an argument for associative learning in the garden pea, Pisum sativum. The garden pea is not specific to a region, but rather grows in cooler, higher altitude climates. Gagliano and colleagues' 2016 paper aims to differentiate between innate phototropism behavior and learned behaviors.[32] Plants use light cues in various ways, such as to sustain their metabolic needs and to maintain their internal circadian rhythms. Circadian rhythms in plants are modulated by endogenous bioactive substances that encourage leaf-opening and leaf-closing and are the basis of nyctinastic behaviors.[98]

Gagliano and colleagues constructed a classical conditioning test in which pea seedlings were divided into two experimental categories and placed in Y-shaped tubes.[32] In a series of training sessions, the plants were exposed to light coming down different arms of the tube. In each case, there was a fan blowing lightly down the tube in either the same or opposite arm as the light. The unconditioned stimulus (US) was the predicted occurrence of light and the conditioned stimulus (CS) was the wind blowing by the fan. Previous experimentation shows that plants respond to light by bending and growing towards it through differential cell growth and division on one side of the plant stem mediated by auxin signaling pathways.[99]

During the testing phase of Gagliano's experiment, the pea seedlings were placed in different Y-pipes and exposed to the fan alone. Their direction of growth was subsequently recorded. The 'correct' response by the seedlings was deemed to be growing into the arm where the light was "predicted" from the previous day. The majority of plants in both experimental conditions grew in a direction consistent with the predicted location of light based on the position of the fan the previous day.[32] For example, if the seedling was trained with the fan and light coming down the same arm of the Y-pipe, the following day the seedling grew towards the fan in the absence of light cues despite the fan being placed in the opposite side of the Y-arm. Plants in the control group showed no preference to a particular arm of the Y-pipe. The percentage difference in population behavior observed between the control and experimental groups is meant to distinguish innate phototropism behavior from active associative learning.[32]

While the physiological mechanism of associative learning in plants is not known, Telewski et al. describes a hypothesis that describes photoreception as the basis of mechano-perception in plants.[100] One mechanism for mechano-perception in plants relies on MS ion channels and calcium channels. Mechanosensory proteins in cell lipid bilayers, known as MS ion channels, are activated once they are physically deformed in response to pressure or tension. Ca2+ permeable ion channels are "stretch-gated" and allow for the influx of osmolytes and calcium, a well-known second messenger, into the cell. This ion influx triggers a passive flow of water into the cell down its osmotic gradient, effectively increasing turgor pressure and causing the cell to depolarize.[100] Gagliano hypothesizes that the basis of associative learning in Pisum sativum is the coupling of mechanosensory and photosensory pathways and is mediated by auxin signaling pathways. The result is directional growth to maximize a plant's capture of sunlight.[32]

Gagliano et al. published another paper on habituation behaviors in the mimosa pudica plant whereby the innate behavior of the plant was diminished by repeated exposure to a stimulus.[18] There has been controversy around this paper and more generally around the topic of plant cognition. Charles Abrahmson, a psychologist and behavioral biologist, says that part of the issue of why scientists disagree about whether plants have the ability to learn is that researchers do not use a consistent definition of "learning" and "cognition".[101] Similarly, Michael Pollan, an author, and journalist, says in his piece The Intelligent Plant that researchers do not doubt Gagliano's data but rather her language, specifically her use of the term "learning" and "cognition" with respect to plants.[102] A direction for future research is testing whether circadian rhythms in plants modulate learning and behavior and surveying researchers' definitions of "cognition" and "learning".

Machine learning

[edit]
Robots can learn to cooperate.

Machine learning, a branch of artificial intelligence, concerns the construction and study of systems that can learn from data. For example, a machine learning system could be trained on email messages to learn to distinguish between spam and non-spam messages. Most of the Machine Learning models are based on probabilistic theories where each input (e.g. an image ) is associated with a probability to become the desired output.

Types

[edit]

Phases

[edit]

See also

[edit]
  • 21st century skills – Skills identified as being required for success in the 21st century
  • Anticipatory socialization – Process in which people take on the values of groups that they aspire to join
  • Epistemology – Philosophical study of knowledge
  • Implicit learning – in learning psychology
  • Instructional theory – Theory that offers explicit guidance on how to better help people learn and develop
  • Learning sciences – Critical theory of learning
  • Lifelong learning – Ongoing, voluntary, and self-motivated pursuit of knowledge
  • Living educational theory
  • Media psychology – Area of psychology
  • Subgoal labeling – Cognitive process

Information theory

[edit]
  • Algorithmic information theory – Subfield of information theory and computer science
  • Algorithmic probability – mathematical method of assigning a prior probability to a given observation
  • Bayesian inference – Method of statistical inference
  • Inductive logic programming – learning logic programs from data
  • Inductive probability – Determining the probability of future events based on past events
  • Information theory – Scientific study of digital information
  • Minimum description length – Model selection principle
  • Minimum message length – Formal information theory restatement of Occam's Razor
  • Occam's razor – Philosophical problem-solving principle
  • Solomonoff's theory of inductive inference – A mathematical theory
  • AIXI – Mathematical formalism for artificial general intelligence

Types of education

[edit]
  • Autodidacticism – Independent education without the guidance of teachers
  • Andragogy – Methods and principles in adult education
  • Pedagogy – Theory and practice of education

References

[edit]
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Notes

[edit]
  • Mayer, R.E. (2001). Multimedia learning. New York: Cambridge University Press. ISBN 978-0-521-78749-9.
  • Paivio, A. (1971). Imagery and verbal processes. New York: Holt, Rinehart, and Winston. ISBN 978-0-03-085173-5.

Further reading

[edit]
  • Ulrich Boser (2019). Learn Better: Mastering the Skills for Success in Life, Business, and School, or How to Become an Expert in Just About Anything. Rodale Books. ISBN 978-0593135310.
[edit]
  • How People Learn: Brain, Mind, Experience, and School (expanded edition) published by the National Academies Press
  • Applying Science of Learning in Education: Infusing Psychological Science into the Curriculum published by the American Psychological Association